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At least 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A BASIS FOR MODIFYING THE TANK 12 COMPOSITE SAMPLING DESIGN

The SRR sampling campaign to obtain residual solids material from the Savannah River Site (SRS) Tank Farm Tank 12 primary vessel resulted in obtaining appreciable material in all 6 planned source samples from the mound strata but only in 5 of the 6 planned source samples from the floor stratum. Consequently, the design of the compositing scheme presented in the Tank 12 Sampling and Analysis Plan, Pavletich (2014a), must be revised. Analytical Development of SRNL statistically evaluated the sampling uncertainty associated with using various compositing arrays and splitting one or more samples for compositing. The variance of the simple mean of composite sample concentrations is a reasonable standard to investigate the impact of the following sampling options. Composite Sample Design Option (a). Assign only 1 source sample from the floor stratum and 1 source sample from each of the mound strata to each of the composite samples. Each source sample contributes material to only 1 composite sample. Two source samples from the floor stratum would not be used. Composite Sample Design Option (b). Assign 2 source samples from the floor stratum and 1 source sample from each of the mound strata to each composite sample. This infers that one source sample from the floor must be used twice, with 2 composite samples sharing material from this particular source sample. All five source samples from the floor would be used. Composite Sample Design Option (c). Assign 3 source samples from the floor stratum and 1 source sample from each of the mound strata to each composite sample. This infers that several of the source samples from the floor stratum must be assigned to more than one composite sample. All 5 source samples from the floor would be used. Using fewer than 12 source samples will increase the sampling variability over that of the Basic Composite Sample Design, Pavletich (2013). Considering the impact to the variance of the simple mean of the composite sample concentrations, the recommendation is to construct each sample composite using four or five source samples. Although the variance using 5 source samples per composite sample (Composite Sample Design Option (c)) was slightly less than the variance using 4 source samples per composite sample (Composite Sample Design Option (b)), there is no practical difference between those variances. This does not consider that the measurement error variance, which is the same for all composite sample design options considered in this report, will further dilute any differences. Composite Sample Design Option (a) had the largest variance for the mean concentration in the three composite samples and should be avoided. These results are consistent with Pavletich (2014b) which utilizes a low elevation and a high elevation mound source sample and two floor source samples for each composite sample. Utilizing the four source samples per composite design, Pavletich (2014b) utilizes aliquots of Floor Sample 4 for two composite samples.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1981

Spherical harmonic analysis of a model-generated climatology

Monthly mean fields of 850 mb temperature (T850), 500 mb geopotential height (G500) and sea level pressure (SLP) were generated in the course of a five-year climate simulation run with a global general circulation model. Both the model-generated climatology and an observed climatology were subjected to spherical harmonic analysis, with separate analyses of the globe and the Northern Hemisphere. Comparison of the dominant harmonics of the two climatologies indicates that more than 95% of the area-weighted spatial variance of G500 and more than 90% of that of T850 are explained by fewer than three components, and that the model adequately simulates these large-scale characteristics. On the other hand, as many as 25 harmonics are needed to explain 95% of the observed variance of SLP, and the model simulation of this field is much less satisfactory. The model climatology is also evaluated in terms of the annual cycles of the dominant harmonics.

Christidis, Z. D.↗
NASA NTRS1983

Effect of scene illumination conditions on digital enhancement techniques of multispectral scanner LANDSAT images

Two sets of MSS/LANDSAT data with solar elevation ranging from 22 deg to 41 deg were used at the Image-100 System to implement the Eliason et alii technique for extracting the topographic modulation component. An unsupervised cluster analysis was used to obtain an average brightness image for each channel. Analysis of the enhanced imaged shows that the technique for extracting topographic modulation component is more appropriated to MSS data obtained under high sun elevation ngles. Low sun elevation increases the variance of each cluster so that the average brightness doesn't represent its albedo proprties. The topographic modulation component applied to low sun elevation angle damages rather than enhance topographic information. Better results were produced for channels 4 and 5 than for channels 6 and 7.

Parada, N. D. J.↗
NASA NTRS1990

Mesospheric momentum fluxes observed by the MST radar at Poker Flat, Alaska

An analysis of the wave motions observed with the Poker Flat MST radar during the winter, summer, and fall of 1986 is presented. Monthly and daily mean winds, momentum fluxes, and velocity variances are investigated in detail. While several features are in agreement with previous measurements, some significant differences also are found to exist in the observations. Monthly mean horizontal winds between 82 and 89 km have amplitudes of 20-40 m/s westward and 10-25 m/s southward in July and August. In fall and winter, the horizontal winds between 58 and 75 km are weaker and essentially eastward.

Wang, Ding-Yi↗
NASA NTRS2015

Spectral Analysis of Forecast Error Investigated with an Observing System Simulation Experiment

The spectra of analysis and forecast error are examined using the observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASAGMAO). A global numerical weather prediction model, the Global Earth Observing System version 5 (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation, is cycled for two months with once-daily forecasts to 336 hours to generate a control case. Verification of forecast errors using the Nature Run as truth is compared with verification of forecast errors using self-analysis; significant underestimation of forecast errors is seen using self-analysis verification for up to 48 hours. Likewise, self analysis verification significantly overestimates the error growth rates of the early forecast, as well as mischaracterizing the spatial scales at which the strongest growth occurs. The Nature Run-verified error variances exhibit a complicated progression of growth, particularly for low wave number errors. In a second experiment, cycling of the model and data assimilation over the same period is repeated, but using synthetic observations with different explicitly added observation errors having the same error variances as the control experiment, thus creating a different realization of the control. The forecast errors of the two experiments become more correlated during the early forecast period, with correlations increasing for up to 72 hours before beginning to decrease.

OSSE↗
DOE OSTI2017

A Piecewise Local Partial Least Squares (PLS) Method for the Quantitative Analysis of Plutonium Nitrate Solutions

We have developed a piecewise local (PL) partial least squares (PLS) analysis method for total plutonium measurements by absorption spectroscopy in nitric acid-based nuclear material processing streams. Instead of using a single PLS model that covers all expected solution conditions, the method selects one of several local models based on an assessment of solution absorbance, acidity, and Pu oxidation state distribution. The local models match the global model for accuracy against the calibration set, but were observed in several instances to be more robust to variations associated with measurements in the process. The improvements are attributed to the relative parsimony of the local models. Not all of the sources of spectral variation are uniformly present at each part of the calibration range. Thus, the global model is locally overfitting and susceptible to increased variance when presented with new samples. A second set of models quantifies the relative concentrations of Pu(III), (IV), and (VI). Standards containing a mixture of these species were not at equilibrium due to a disproportionation reaction. Therefore, a separate principal component analysis is used to estimate of the concentrations of the individual oxidation states in these standards in the absence of independent confirmatory analysis. The PL analysis approach is generalizable to other systems where the analysis of chemically complicated systems can be aided by rational division of the overall range of solution conditions into simpler sub-regions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Nuclear data uncertainty propagation applied to the versatile test reactor conceptual design

We report the Versatile Test Reactor (VTR) currently under development is a 300 MWth sodium-cooled fast reactor (SFR) fueled with ternary metal alloy fuel, which aims to accelerate the testing of advanced nuclear fuels, materials, instrumentation, and sensors in high flux environments that are necessary to license the next generation of advanced reactor concepts. To support the VTR design process, uncertainties associated with the nuclear data has been propagated through the reactor core neutronics calculation to global parameters of interest, such as the core multiplication factor, kinetic parameters, and various reactivity feedback coefficients, following the sensitivity based uncertainty propagation approach. By folding the sensitivity coefficients, separately computed by the generalized perturbation theory code PERSENT and Monte Carlo code Serpent 2, with the variance-covariance matrices from COMMARA-2.0, we obtain the reaction-wise, isotope-wise, and overall uncertainties for each response of interest due to nuclear data uncertainty. With Serpent 2, the statistical error of the uncertainty is obtained by propagating the statistical error of the sensitivity coefficients through the same process using a newly developed uncertainty propagation method. From both codes, the overall top uncertainty contributors are found to be the cross section of Fe-56 elastic scattering, Na-23 elastic scattering, and U 238 inelastic scattering. The large contributions of the Fe-56 elastic scattering cross sections to global parameters are due to its relatively large relative uncertainty of 5–10% in nuclear data and the large volume of Fe-containing reflector assemblies in the fairly compact VTR core design. Both codes agreed well for the overall uncertainty estimates of all responses of interest, except the delayed neutron fraction, prompt neutron generation time, and the coolant density feedback coefficient, where Serpent 2 yielded a much larger value than PERSENT due to the large statistical error of sensitivity coefficients. The calculated uncertainties are also compared to those associated with other SFR cores. Another outcome of this study is a variance-covariance matrix of reactivity coefficients, which can be used in the subsequent uncertainty propagation to the system level to investigate the impact of identified uncertainties on system responses in the safety analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Plasmonic Conducting Metal Oxide-Based Optical Fiber Sensors for Chemical and Intermediate Temperature-Sensing Applications

The demand for real-time sensors in harsh environments at elevated temperature is significant and increasing. In this manuscript, the chemical and temperature sensing using the optical response through the practical fiber platform is demonstrated, and principle component analysis is coupled with targeted experimental film characterization to understand the fundamental sensing layer properties, which dominate measured gas sensing responses in complex gas mixtures. More specifically, tin-doped indium oxide-decorated sensors fabricated with the sol–gel method show stable and stepwise transmission responses varying over a wide range of H2 concentration (5–100%) at 250–350 °C as well as responses to CH4 and CO to a lesser extent. Measured responses are attributed to modifications to the surface plasmon resonance absorption in the near-infrared range and are dominated by the highest concentrations of the most-reducing analyte based upon systematic mixed gas stream experiments. Principal component analysis is utilized for this type of sensor to improve the quantitative and qualitative understanding of responses, clearly identifying that the dominant principle component (PC #1) accounts for ~78% of total data variance. Correlations between PC #1 and the experimentally derived free carrier concentration confirm that this material property plays the strongest role on the ITO gas sensing mechanism, while correlations between the free carrier mobility and the second most important principle component (PC #2) suggest that this quantity may play a significant but secondary role. As such, the results presented here clarify the relationship between generalized principle components and fundamental sensing materials properties thereby suggesting the pathway toward improved multicomponent gas speciation through sensor layer engineering. Furthermore, the work presented represents a significant step toward the ultimate objective of optical waveguide sensors integrated with multivariate data analytics for multiparameter monitoring with a single sensor element.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Radio efficiency of pulsars

We investigate radio emission efficiency, ξ, of pulsars and report a near-linear inverse correlation between ξ and the spin-down power, E-dot , as well as a near-linear correlation between ξ and pulsar age, τ. This is a consequence of very weak, if any, dependences of radio luminosity, L, on pulsar period, P, and the period derivative, P-dot , in contrast to X-ray or γ-ray emission luminosities. The analysis of radio fluxes suggests that these correlations are not due to a selection effect, but are intrinsic to the pulsar radio emission physics. We have found that, although with a large variance, the radio luminosity of pulsars is ≈10{sup 29} erg s{sup –1}, regardless of the position in the P-- P-dot diagram. Within such a picture, a model-independent statement can be made that the death line of radio pulsars corresponds to an upper limit in the efficiency of radio emission. If we introduce the maximum value for radio efficiency into the Monte Carlo-based population syntheses we can reproduce the observed sample using the random luminosity model. Using the Kolmogorov-Smirnov test on a synthetic flux distribution reveals a high probability of reproducing the observed distribution. Our results suggest that the plasma responsible for generating radio emission is produced under similar conditions regardless of pulsar age, dipolar magnetic field strength, and spin-down rate. The magnetic fields near the pulsar surface are likely dominated by crust-anchored, magnetic anomalies, which do not significantly differ among pulsars, leading to similar conditions for generating electron-positron pairs necessary to power radio emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Tracing the green valley with entropic thresholding

ABSTRACT The green valley represents the population of galaxies that are transitioning from the actively star-forming blue cloud to the passively evolving red sequence. Studying the properties of the green valley galaxies is crucial for our understanding of the exact mechanisms and processes that drive this transition. The green valley does not have a universally accepted definition. The boundaries of the green valley are often determined by empirical lines that are subjective and vary across studies. We present an unambiguous definition of the green valley in the colour–stellar mass plane using the entropic thresholding. We first divide the galaxy population into the blue cloud and the red sequence based on a colour threshold that minimizes the intraclass variance and maximizes the interclass variance. Our method splits the region between the mean colours of the blue cloud and the red sequence into three parts by maximizing the total entropy of that region. We repeat our analysis in a number of independent stellar mass bins to define the boundaries of the green valley in the colour–mass diagram. Our method provides a robust and natural definition of the green valley.

Pandey, Biswajit (ORCID:000000017876595X)↗
DOE OSTI2018

Reassessment of Resuspension Factor Following Radionuclide Dispersal: Toward a General-purpose Rate Constant

A recent analysis of historical radionuclide resuspension datasets confirmed the general applicability of the Anspaugh and modified Anspaugh models of resuspension factors following both controlled and disastrous releases. While observations appear to have larger variance earlier in time, previous studies equally weighted the data for statistical fit calculations; this could induce a positive skewing of resuspension coefficients in the early time-period. A refitting is performed using a relative instrumental weighting of the observations. Measurements within a 3-d window are grouped into singular sample sets to construct standard deviations. The resulting best-fit equations produce tamer exponentials, which give decreased integrated resuspension factor values relative to those reported by Anspaugh. As expected, the fits attenuate greater error among the data at earlier time. In conclusion, the reevaluation provides a sharper contrast between the empirical models and reaffirms their deficiencies in the short-lived timeframe wherein the dynamics of particulate dispersion dominate the resuspension process.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
NASA NTRS1980

Automated frequency standard stability data reduction

A design using a medium sized computer, a fiber optic communication link, and a desk top computer to reduce data collected at a remote site for analysis of frequency standard tests is described. Data generated at the Interim Frequency Standards Test Facility is collected on magnetic tape, which is then transported to a Sigma 5 computer. An Allan variance (two sample variance) is then calculated. The Allan variance (sigma vs tau) is then written to a data file in the Sigma 5. A fiber optic communication link between the Sigma 5 and a desk top computer was designed to transmit data in the Sigma 5 file to the desk top computer. A program was written for the desk top computer that will automatically access the data file in the Sigma 5, process the data and provide a data plot.

Knapp, L. J.↗
NASA NTRS1992

Probabilistic finite elements for fatigue and fracture analysis

Attenuation is focused on the development of Probabilistic Finite Element Method (PFEM), which combines the finite element method with statistics and reliability methods, and its application to linear, nonlinear structural mechanics problems and fracture mechanics problems. The computational tool based on the Stochastic Boundary Element Method is also given for the reliability analysis of a curvilinear fatigue crack growth. The existing PFEM's have been applied to solve for two types of problems: (1) determination of the response uncertainty in terms of the means, variance and correlation coefficients; and (2) determination the probability of failure associated with prescribed limit states.

Belytschko, Ted↗
NASA NTRS2018

Vegetation Change Detection in Southern California Solar Energy Developments

Change detection from satellite sensor vegetation indices (VIs) presents an opportunity to monitor trends and disturbances at the regional scale for southern California's Mojave and Lower Colorado Deserts. Renewable energy sites are being constructed in this region on public lands under the Bureau of Land Management (BLM). We have developed a framework for VI change detection over the past two decades, with initial focus on three sites, Joshua Tree National Park, Mojave National Preserve, and a proximal group of Development Focus Areas (DFAs), for comparison between protected and development-targeted lands. Three Terra MODIS VIs (normalized difference [NDVI], enhanced [EVI], soil-adjusted [SAVI]) were evaluated in the Breaks for Additive Season and Trend (BFAST) setting for the regional MODIS 250-m resolution grid to estimate significant time series shifts (breakpoints) from February 2000 to May 2018. All three VIs tended to detect the maximum number of breakpoints at a grid location, but cross-correlations with precipitation and comparison with timing of wildfire burns near the study sites for breakpoint density (proportion of area with a breakpoint) showed that NDVI had the strongest response to these major disturbances, supporting its use for subsequent analysis. Time series of NDVI breakpoint change densities for individual solar energy sites did not have a consistent vegetation response following construction. Bootstrapping showed that the DFAs had significantly larger kurtosis and variance in the positive NDVI breakpoint distribution than did the protected sites, but there was no significant difference in the negative distribution for all three sites. The inconsistent post-construction NDVI signal and the large number of breakpoints overall suggested that the largest changes in vegetation cover density were tied to seasonal precipitation amounts. The distributional results indicated that existing site-specific conditions were the main control on VI responses, given the history of human disturbances in the DFAs. Although the results do not support persistent VI disturbances resulting from recent solar energy development, continued monitoring and examination of other ecological variables and surface temperatures will be vital to the long-term protection of this desert environment.

Potter, Christopher S.↗
DOE OSTI2017

Sensitivity analysis of VERA-CS and FRAPCON coupling in a multiphysics environment

A demonstration and description of the LOCA Toolkit for US light water reactors (LOTUS) is presented. Through LOTUS, the core simulator VERA-CS developed by CASL is coupled with the fuel performance code FRAPCON. The coupling is performed with consistent uncertainty propagation with all model inconsistencies being well-documented. Monte Carlo sampling is performed on a single 17 × 17 fuel assembly with a three cycle depletion case. Both uncertainty quantification (UQ) and sensitivity analysis (SA) are used at multiple states within the simulation to elucidate the behavior of minimum departure from nucleate boiling ratio (MDNBR), maximum fuel centerline temperature (MFCT), and gap conductance at peak power (GCPP). The SA metrics used are the Pearson correlation coefficient, Sobol sensitivity indices, and the density-based, delta moment independent measures. Results for MDNBR show consistency among all SA measures, as well for all states throughout the fuel lifecycle. MFCT results contain consistent rankings between SA measures, but show differences throughout the lifecycle. GCPP exhibits predominantly linear relations at low and high burnup, but highly nonlinear relations at intermediate burnup due to abrupt shifts between models. As a result, such behavior is largely undetectable to traditional regression or variance-based methods and demonstrates the utility of density-based methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Non-Gaussian structure of B-mode polarization after delensing

The B-mode polarization of the cosmic microwave background on large scales has been considered as a probe of gravitational waves from the cosmic inflation. Ongoing and future experiments will, however, suffer from contamination due to the B-modes of non-primordial origins, one of which is the lensing induced B-mode polarization. Subtraction of the lensing B-modes, usually referred to as delensing, will be required for further improvement of detection sensitivity of the gravitational waves. In such experiments, knowledge of statistical properties of the B-modes after delensing is indispensable to likelihood analysis particularly because the lensing B-modes are known to be non-Gaussian. In this paper, we study non-Gaussian structure of the delensed B-modes on large scales, comparing it with that of the lensing B-modes. In particular, we investigate the power spectrum correlation matrix and the probability distribution function (PDF) of the power spectrum amplitude. Assuming an experiment in which the quadratic delensing is an almost optimal method, we find that delensing reduces correlations of the lensing B-mode power spectra between different multipoles, and that the PDF of the power spectrum amplitude is well described as a normal distribution function with a variance larger than that in the case of a Gaussian field. These features are well captured by an analytic model based on the 4th order Edgeworth expansion. As a consequence of the non-Gaussianity, the constraint on the tensor-to-scalar ratio after delensing is degraded within approximately a few percent, which depends on the multipole range included in the analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.

09 BIOMASS FUELS↗