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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Study of Plastic Scintillator Properties for Radioactive Sources Dosimetry - Paper 108

Plastic scintillator is a simple material which has the density close to that of human soft tissue (1.06 g/cm{sup 3}). Its energy response is close to that of human soft tissue and it is relatively energy independent. This prospect provide a desired characteristics in measuring dose by plastic scintillator either for radiation monitoring or personal dosimeter. Generally the energy calibration of organic scintillator will be done by using gamma ray sources. The positions of Compton edge in pulse height spectra, which have known energy values will be identified. However the Compton edge normally is very broad and difficult to determine the point corresponding to that particular Compton electron energies. Many researchers used several fitting functions and Monte Carlo simulations to determine the position of Compton edge. For example, Proctor and Wellman (2012) used a straight line fit to the linear part of Compton edge and extrapolated to zero count. While L. Swiderski et al. used a method based on a back-scattered coincidence measurement to measure in a wide energy range the position of Compton edge in organic scintillators. For a simple and quick approach of calibration, we used a Gauss-error function to fit the Compton edge region of interest by assumed that the location of maximum energy of Compton electrons is half-height of the Compton maximum (CM). The reasons is because the CM position could be determined easily from the spectra throughout wide energy range. Interpreting gamma dose rates from accumulated plastic scintillation detector spectra is often a complex task because the probability of a full energy deposition event in the detector is often negligible. Despite no full energy peaks in plastic scintillator spectra, several attempts have been made by the other researchers to obtain the dose from the energy distribution spectra of gamma radiation. For example, Proctor and Wellman used the modified spectrum dose index (SDI) to calculate the exposure rates by multiplying the energy corresponding to its channel and all products are summed before multiply by a calibration constant to yield an exposure rate. While Lobdell and Hertel calculated dose using a response matrix based on spectral unfolding technique. From these points of view, we have made an attempt to correlate the counts obtained in scintillator with absorbed dose or ambient dose equivalent. We aimed to calibrate the plastic scintillator energy deposition for dose, by correlate the counts obtained with a particular value of dose. By designed the scintillator to measure at 1 cm tissue depth might be helpful to be used as radiation monitoring or personal dosimeter since the energy response of plastic scintillator is relatively energy independent compared to that of inorganic scintillators. The energy calibration proposed from simple fitting approach had been verified with calculated spectra. This might be considered as a practical approach for technician or radiation workers with sufficient accuracy. The linear behavior of counts per absorbed dose give promising to calibrate scintillator energy deposition to read dose (equivalent dose or absorbed dose) for photons. Thus the scintillator could provide both the energy and dose response simultaneously, which may important in some radiation field of measurements. Currently the scintillator is able to give dose rate value for gamma sources of Cs-137 and Mn-54. The number of counts per unit absorbed dose would likely to vary somewhat with photon energy, although the plastic scintillator should have a tissue dose response that is relatively energy independent. Further analysis will be done on conversion factor parameters so that it could be used in such situations where the radiation field is complex or unknown. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2010

Nonlinear Gyrokinetics: A Powerful Tool for the Description of Microturbulence in Magnetized Plasmas

Gyrokinetics is the description of low-frequency dynamics in magnetized plasmas. In magnetic-confinement fusion, it provides the most fundamental basis for numerical simulations of microturbulence; there are astrophysical applications as well. In this tutorial, a sketch of the derivation of the novel dynamical system comprising the nonlinear gyrokinetic (GK) equation (GKE) and the coupled electrostatic GK Poisson equation will be given by using modern Lagrangian and Lie perturbation methods. No background in plasma physics is required in order to appreciate the logical development. The GKE describes the evolution of an ensemble of gyrocenters moving in a weakly inhomogeneous background magnetic field and in the presence of electromagnetic perturbations with wavelength of the order of the ion gyroradius. Gyrocenters move with effective drifts, which may be obtained by an averaging procedure that systematically, order by order, removes gyrophase dependence. To that end, the use of the Lagrangian differential one-form as well as the content and advantages of Lie perturbation theory will be explained. The electromagnetic fields follow via Maxwell's equations from the charge and current density of the particles. Particle and gyrocenter densities differ by an important polarization effect. That is calculated formally by a "pull-back" (a concept from differential geometry) of the gyrocenter distribution to the laboratory coordinate system. A natural truncation then leads to the closed GK dynamical system. Important properties such as GK energy conservation and fluctuation noise will be mentioned briefly, as will the possibility (and diffculties) of deriving nonlinear gyro fluid equations suitable for rapid numerical solution -- although it is probably best to directly simulate the GKE. By the end of the tutorial, students should appreciate the GKE as an extremely powerful tool and will be prepared for later lectures describing its applications to physical problems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Uncertainty and Sensitivity Analyses of a Pebble Bed HTGR Loss of Cooling Event

The Very High Temperature Reactor Methods Development group at the Idaho National Laboratory identified the need for a defensible and systematic uncertainty and sensitivity approach in 2009. This paper summarizes the results of an uncertainty and sensitivity quantification investigation performed with the SUSA code, utilizing the International Atomic Energy Agency CRP 5 Pebble Bed Modular Reactor benchmark and the INL code suite PEBBED-THERMIX. Eight model input parameters were selected for inclusion in this study, and after the input parameters variations and probability density functions were specified, a total of 800 steady state and depressurized loss of forced cooling (DLOFC) transient PEBBED-THERMIX calculations were performed. The six data sets were statistically analyzed to determine the 5% and 95% DLOFC peak fuel temperature tolerance intervals with 95% confidence levels. It was found that the uncertainties in the decay heat and graphite thermal conductivities were the most significant contributors to the propagated DLOFC peak fuel temperature uncertainty. No significant differences were observed between the results of Simple Random Sampling (SRS) or Latin Hypercube Sampling (LHS) data sets, and use of uniform or normal input parameter distributions also did not lead to any significant differences between these data sets.

Strydom, Gerhard↗
DOE OSTI2020

Three-State Majority-vote Model on Scale-Free Networks and the Unitary Relation for Critical Exponents

Abstract We investigate the three-state majority-vote model for opinion dynamics on scale-free and regular networks. In this model, an individual selects an opinion equal to the opinion of the majority of its neighbors with probability 1 − q , and different to it with probability q . The parameter q is called the noise parameter of the model. We build a network of interactions where z neighbors are selected by each added site in the system, a preferential attachment network with degree distribution k − λ , where λ = 3 for a large number of nodes N . In this work, z is called the growth parameter. Using finite-size scaling analysis, we obtain that the critical exponents $$\beta /\bar{\nu }$$ β / ν ¯ and $$\gamma /\bar{\nu }$$ γ / ν ¯ associated with the magnetization and the susceptibility, respectively. Using Monte Carlo simulations, we calculate the critical noise parameter q c as a function of z for the scale-free networks and obtain the phase diagram of the model. We find that the critical exponents add up to unity when using a special volumetric scaling, regardless of the dimension of the network of interactions. We verify this result by obtaining the critical noise and the critical exponents for the two and three-state majority-vote model on cubic lattice networks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Arctic Shrub Expansion, Plant Functional Trait Variation, and Effects on Belowground Carbon Cycling (Final Technical Report)

Terrestrial ecosystems are undergoing dramatic changes in response to climate warming, and these changes are expected to feedback to the atmosphere, potentially altering the trajectory of future climate change. Feedbacks from Arctic ecosystems are a major concern because the Arctic is projected to warm significantly in the 21 st century and because >50% of global belowground organic carbon is stored in permafrost and overlying soils. Warming-driven release of this carbon could drastically increase atmospheric greenhouse gas concentrations and accelerate climate warming. Plant communities are also responding to warming, as evidenced by the widely documented increase in woody-shrub growth and “greening” across much of the Arctic tundra biome. This vegetation shift may offset or amplify warming by altering carbon cycling. The direction and magnitude of shrub effects remain highly uncertain, however, due to limited understanding of the consequences of shrub expansion for belowground carbon cycling and simplification of these relationships in models. The major shrubs expanding in the Arctic (Betula, Salix, and Alnus) vary widely with respect to aboveground and belowground traits (e.g., tissue production and chemistry, rooting depth, microbial symbionts), and may also exhibit substantial intraspecific variation in these traits in response to environmental conditions. Such variation is likely to have profound implications for soil carbon cycling. The overarching goal of this project was to improve process-based understanding of the influence of shrub expansion on carbon cycling to enable improved representation of carbon dynamics in ecosystem and Earth system models. We investigated how plant functional traits vary among shrub genera, respond to environmental conditions, and affect belowground carbon and nutrient cycling by quantifying relationships among functional traits and biogeochemical cycling along edaphic gradients nested within a climate gradient in the Alaskan tundra. We found consistent differences in leaf and root traits among shrub genera and between shrubs and a widespread sedge species, indicating diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs. We also found striking differences in trait values among individuals within the same species or genera within sites. Soil parameters were more important than climate parameters for predicting size and leaf trait variation, and root trait responses were less dependent on climate overall. For all but one root trait, including parameters representing aboveground traits improved the predictive ability of models. These results demonstrate that tundra shrub traits vary considerably at local scales and soil factors drive this variation, especially belowground. Furthermore, leveraging information about aboveground traits and soil conditions can improve predictions of how belowground traits will respond to climate change. Despite these differences, soil carbon and nitrogen pools in the active layer did not vary among plots dominated by different shrub or sedge genera. Instead, pool sizes generally decreased from warmer to colder sites, consistent with a productivity gradient. Patterns of isotopic N composition indicate that shrubs tighten nitrogen cycling via nitrogen resorption or immobilization of shrub litter. Overall, these results suggest that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic. We also performed simulation experiments with the Terrestrial Ecosystem Model (TEM) incorporated in the Predictive Ecosystem Analyzer (PEcAn) framework, treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We performed simulations across different types of tundra, including shrub tundra. One key finding was that both model sensitivity and uncertainty to a given parameter could vary within the same type of tundra, but in a different geographical location, such as over the climate gradient of shrub tundra described above. We organized a special session at the annual meeting of the Ecological Society of America in August 2019 to disseminate our results, refine recommendations for model improvement, and initiate collaborations to implement these recommendations in existing models of tundra carbon dynamics at ecosystem to Earth system scales. Our results support DOE near-term priorities by providing mechanistic insights into the role of vegetation change in the terrestrial carbon cycle in a region that is inadequately represented in Earth system models. Current models reduce the complexity of Arctic vegetation to a small number of plant functional types (PFTs). This approach implicitly assumes that each PFT represents the average ecological function of its constituent species, thus ignoring the effects of trait variation on biogeochemical cycling and potentially leading to large uncertainty in the sign and magnitude of ecosystem feedbacks to climate. By quantifying variation of plant functional traits across broad gradients of climatic and edaphic conditions and elucidating the linkages of such variation with carbon and nutrient cycling, our results illustrate the need and create a foundation for further developing trait-based modeling approaches that allow the traits of PFTs to vary as a function of environmental conditions. These approaches should improve the capacity of simulation models to offer insights into ecosystem carbon dynamics associated with novel plant communities in a rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data-driven Minimum Entropy Control for Stochastic Nonlinear Systems using the Cumulant-Generating Function

Here, we present a novel minimum entropy control algorithm for a class of stochastic nonlinear systems subjected to non-Gaussian noises. The entropy control can be considered as an optimization problem for the system randomness attenuation, but the mean value has to be considered separately. To overcome this disadvantage, a new representation of the system stochastic properties was given using the cumulant-generating function based on the moment-generating function, in which the mean value and the entropy was reflected by the shape of the cumulant-generating function. Based on the samples of the system output and control input, a time-variant linear model was identified, and the minimum entropy optimization was transformed to system stabilization. Then, an optimal control strategy was developed to achieve the randomness attenuation, and the boundedness of the controlled system output was analyzed. The effectiveness of the presented control algorithm was demonstrated by a numerical example. In this paper, a data-driven minimum entropy design is presented without pre-knowledge of the system model; entropy optimization is achieved by the system stabilization approach in which the stochastic distribution control and minimum entropy are unified using the same identified structure; and a potential framework is obtained since all the existing system stabilization methods can be adopted to achieve the minimum entropy objective.

42 ENGINEERING↗
DOE OSTI2011

ARE ALL SHORT-HARD GAMMA-RAY BURSTS PRODUCED FROM MERGERS OF COMPACT STELLAR OBJECTS?

The origin and progenitors of short-hard gamma-ray bursts (GRBs) remain a puzzle and a highly debated topic. Recent Swift observations suggest that these GRBs may be related to catastrophic explosions in degenerate compact stars, denoted as 'Type I' GRBs. The most popular models include the merger of two compact stellar objects (NS-NS or NS-BH). We utilize a Monte Carlo approach to determine whether a merger progenitor model can self-consistently account for all the observations of short-hard GRBs, including a sample with redshift measurements in the Swift era (z-known sample) and the CGRO/BATSE sample. We apply various merger time delay distributions invoked in compact star merger models to derive the redshift distributions of these Type I GRBs, and then constrain the unknown luminosity function of Type I GRBs using the observed luminosity-redshift (L-z) distributions of the z-known sample. The best luminosity function model, together with the adopted merger delay model, is then applied to confront the peak flux distribution (log N-log P distribution) of the BATSE and Swift samples. We find that for all the merger models invoking a range of merger delay timescales (including those invoking a large fraction of 'prompt mergers'), it is difficult to reconcile the models with all the data. The data are instead statistically consistent with the following two possible scenarios. First, that short/hard GRBs are a superposition of compact-star-merger-origin (Type I) GRBs and a population of GRBs that track the star formation history, which are probably related to the deaths of massive stars (Type II GRBs). Second, the entire short/hard GRB population is consistent with a typical delay of 2 Gyr with respect to the star formation history with modest scatter. This may point toward a different Type I progenitor than the traditional compact star merger models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Local structure in BaTi O 3 - BiSc O 3 dipole glasses

Local structures in cubic perovskite-type (Ba 0.6 Bi 0.4 )(Ti 0.6 Sc 0.4 )O 3 solid solutions that exhibit reentrant dipole glass behavior have been studied with variable-temperature x-ray/neutron total scattering, extended x-ray absorption fine structure, and electron diffraction methods. Simultaneous fitting of these data using a reverse Monte Carlo algorithm provided instantaneous atomic configurations, which have been used to extract local displacements of the constituent species. The smaller Bi and Ti atoms exhibit probability density distributions that consist of 14 and 8 split sites, respectively. In contrast, Ba and Sc feature single-site distributions. The multisite distributions arise from large and strongly anisotropic off-center displacements of Bi and Ti. The cation displacements are correlated over a short range, with a correlation length limited by chemical disorder. The magnitudes of these displacements and their anisotropy, which are largely determined by local chemistry, change relatively insignificantly on cooling from room temperature. The structure features a nonrandom distribution of local polarization with low-dimensional polar clusters that are several unit cells in size. In situ measurements of atomic pair-distribution function under applied electric field were used to study field-induced changes in the local structure; however, no significant effects besides lattice expansion in the direction of the field could be observed up to electric-field values of 4 kVmm -1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The evolution of galaxy shapes in CANDELS: from prolate to discy

In this study, we model the projected b/a – log a distributions of CANDELS star-forming main-sequence galaxies, where a (b) is the half-light semimajor (semiminor) axis of the galaxy images measured by GALFIT . We find that smaller a galaxies are rounder at all stellar masses M* and redshifts, so we include a when analysing b/a distributions. Approximating intrinsic shapes of the galaxies as triaxial ellipsoids and assuming a multivariate normal distribution of galaxy size and two shape parameters, we construct their intrinsic shape and size distributions to obtain the fractions of elongated (prolate), discy (oblate), and spheroidal galaxies in each redshift and mass bin. We find that galaxies tend to be prolate at low M* and high redshifts, and discy at high M* and low redshifts, qualitatively consistent with van der Wel et al., implying that galaxies tend to evolve from prolate to discy. These results are consistent with the predictions from simulations that the transition from prolate to oblate is caused by a compaction event at a characteristic mass range, making the galaxy centre baryon dominated. We give probabilities of a galaxy’s being elongated, discy, or spheroidal as a function of its M* , redshift, and projected b/a and a , which can facilitate target selections of galaxies with specific shapes at high redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Excitation two-center interference and the orbital geometry in laser-induced nonsequential double ionization of diatomic molecules

We address the influence of the molecular orbital geometry and of the molecular alignment with respect to the laser-field polarization on laser-induced nonsequential double ionization of diatomic molecules for different molecular species, namely N{sub 2} and Li{sub 2}. We focus on the recollision excitation with subsequent tunneling ionization (RESI) mechanism, in which the first electron, upon return, promotes the second electron to an excited state, from where it subsequently tunnels. We assume that both electrons are initially in the highest occupied molecular orbital (HOMO) and that the second electron is excited to the lowest unoccupied molecular orbital (LUMO). We show that the electron-momentum distributions exhibit interference maxima and minima due to the electron emission at spatially separated centers. We provide generalized analytical expressions for such maxima or minima, which take into account s-p mixing and the orbital geometry. The patterns caused by the two-center interference are sharpest for vanishing alignment angle and get washed out as this parameter increases. Apart from that, there exist features due to the geometry of the LUMO, which may be observed for a wide range of alignment angles. Such features manifest themselves as the suppression of probability density in specific momentum regions due to the shape of the LUMO wave function, or as an overall decrease in the RESI yield due to the presence of nodal planes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Numerical convergence and validation of the DIMP inverse particle transport model

The data integration with modeled predictions (DIMP) model is a promising inverse radiation transport method for solving the special nuclear material (SNM) holdup problem. Unlike previous methods, DIMP is a completely passive nondestructive assay technique that requires no initial assumptions regarding the source distribution or active measurement time. DIMP predicts the most probable source location and distribution through Bayesian inference and quasi-Newtonian optimization of predicted detector re-sponses (using the adjoint transport solution) with measured responses. DIMP performs well with for-ward hemispherical collimation and unshielded measurements, but several considerations are required when using narrow-view collimated detectors. DIMP converged well to the correct source distribution as the number of synthetic responses increased. DIMP also performed well for the first experimental validation exercise after applying a collimation factor, and sufficiently reducing the source search vol-ume's extent to prevent the optimizer from getting stuck in local minima. DIMP's simple point detector response function (DRF) is being improved to address coplanar false positive/negative responses, and an angular DRF is being considered for integration with the next version of DIMP to account for highly collimated responses. Overall, DIMP shows promise for solving the SNM holdup inverse problem, especially once an improved optimization algorithm is implemented.

42 ENGINEERING↗
DOE OSTI2013

A new approach to detailed structural decomposition from the splash and phat surveys: Kicked-up disk stars in the Andromeda galaxy?

We characterize the bulge, disk, and halo subcomponents in the Andromeda galaxy (M31) over the radial range 4 kpc < R {sub proj} < 225 kpc. The cospatial nature of these subcomponents renders them difficult to disentangle using surface brightness (SB) information alone, especially interior to ∼20 kpc. Our new decomposition technique combines information from the luminosity function (LF) of over 1.5 million bright (20 < m {sub 814W} < 22) stars from the Panchromatic Hubble Andromeda Treasury survey, radial velocities of over 5000 red giant branch stars in the same magnitude range from the Spectroscopic and Photometric Landscape of Andromeda's Stellar Halo survey, and integrated I-band SB profiles from various sources. We use an affine-invariant Markov chain Monte Carlo algorithm to fit an appropriate toy model to these three data sets. The bulge, disk, and halo SB profiles are modeled as a Sérsic, exponential, and cored power law, respectively, and the LFs are modeled as broken power laws. We present probability distributions for each of 32 parameters describing the SB profiles and LFs of the three subcomponents. We find that the number of stars with a disk-like LF is 5.2% ± 2.1% larger than the number with disk-like (dynamically cold) kinematics, suggesting that some stars born in the disk have been dynamically heated to the point that they are kinematically indistinguishable from halo members. This is the first kinematical evidence for a 'kicked-up disk' halo population in M31. The fraction of kicked-up disk stars is consistent with that found in simulations. We also find evidence for a radially varying disk LF, consistent with a negative metallicity gradient in the stellar disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Warm dust around cool stars: field M dwarfs with Wise 12 or 22 μm excess emission

Using the Sloan Digital Sky Survey Data Release 7 (SDSS DR7) spectroscopic catalog, we searched the WISE AllWISE catalog to investigate the occurrence of warm dust, as inferred from IR excesses, around field M dwarfs (dMs). We developed SDSS/WISE color selection criteria to identify 175 dMs (from 70,841) that show IR flux greater than the typical dM photosphere levels at 12 and/or 22 μm, including seven new stars within the Orion OB1 footprint. We characterize the dust populations inferred from each IR excess and investigate the possibility that these excesses could arise from ultracool binary companions by modeling combined spectral energy distributions. Our observed IR fluxes are greater than levels expected from ultracool companions (>3σ). We also estimate that the probability the observed IR excesses are due to chance alignments with extragalactic sources is <0.1%. Using SDSS spectra we measure surface gravity-dependent features (K, Na, and CaH 3) and find <15% of our sample indicates low surface gravities. Examining tracers of youth (Hα, UV fluxes, and Li absorption), we find <3% of our sample appear young, indicating we are observing a population of field stars ≳1 Gyr, likely harboring circumstellar material. We investigate age-dependent properties probed by this sample, studying the disk fraction as a function of Galactic height. The fraction remains small and constant to |Z| ∼ 700 pc and then drops, indicating little to no trend with age. Possible explanations for disks around field dMs include (1) collisions of planetary bodies, (2) tidal disruption of planetary bodies, or (3) failed planet formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Computing an Optimal Entanglement Path with Throughput and Fidelity Considerations

Entanglement distribution is a core function of quantum networks essential for operations including teleportation, distributed quantum sensing, and multisite computation. Entanglement throughput and fidelity are two critical performance measures that depend on the quantum transmission along the links and swapping operations at the repeaters along the path. We study the problem of computing a end-to-end entanglement path that satisfies both fidelity and throughput requirements, leveraging qubit buffers at the nodes and considering the sequential swapping order. We show that the general problem of simultaneously satisfying both metrics to be NP-hard, and develop an algorithm to maximize throughput subject to a given fidelity threshold. We introduce the concepts of entanglement probability distribution and path domination and exploit them in the design of our algorithm. Extensive numerical results show that our algorithm can find optimal solutions in networks with thousands of nodes in less than a second. We also describe practical and possible implementation aspects of this algorithm in terms of devices and architecture support.

Xue, Guoliang [Arizona State University]↗
DOE OSTI2012

Greater Sage-Grouse Habitat Use and Population Demographics at the Simpson Ridge Wind Resource Area, Carbon County, Wyoming

This study was conducted to obtain baseline data on use of the proposed Simpson Ridge Wind Resource Area (SRWRA) in Carbon County, Wyoming by greater sage-grouse. The first two study years were designed to determine pre-construction seasonally selected habitats and population-level vital rates (productivity and survival). The presence of an existing wind energy facility in the project area, the PacifiCorp Seven Mile Hill (SMH) project, allowed us to obtain some information on initial sage-grouse response to wind turbines the first two years following construction. To our knowledge these are the first quantitative data on sage-grouse response to an existing wind energy development. This report presents results of the first two study years (April 1, 2009 through March 30, 2011). This study was selected for continued funding by the National Wind Coordinating Collaborative Sage-Grouse Collaborative (NWCC-SGC) and has been ongoing since March 30, 2011. Future reports summarizing results of this research will be distributed through the NWCC-SGC. To investigate population trends through time, we determined the distribution and numbers of males using leks throughout the study area, which included a 4-mile radius buffer around the SRWRA. Over the 2-year study, 116 female greater sage-grouse were captured by spotlighting and use of hoop nets on roosts surrounding leks during the breeding period. Radio marked birds were located anywhere from twice a week to once a month, depending on season. All radio-locations were classified to season. We developed predictor variables used to predict success of fitness parameters and relative probability of habitat selection within the SRWRA and SMH study areas. Anthropogenic features included paved highways, overhead transmission lines, wind turbines and turbine access roads. Environmental variables included vegetation and topography features. Home ranges were estimated using a kernel density estimator. We developed resource selection functions (RSF) to estimate probability of selection within the SRWRA and SMH. Fourteen active greater sage-grouse leks were documented during lek surveys Mean lek size decreased from 37 in 2008 to 22 in 2010. Four leks located 0.61, 1.3, 1.4 and 2.5 km from the nearest wind turbine remained active throughout the study, but the total number of males counted on these four leks decreased from 162 the first year prior to construction (2008), to 97 in 2010. Similar lek declines were noted in regional leks not associated with wind energy development throughout Carbon County. We obtained 2,659 sage-grouse locations from radio-equipped females, which were used to map use of each project area by season. The sage-grouse populations within both study areas are relatively non-migratory, as radio-marked sage-grouse used similar areas during all annual life cycles. Potential impacts to sage-grouse from wind energy infrastructure are not well understood. The data rom this study provide insight into the early interactions of wind energy infrastructure and sage-grouse. Nest success and brood-rearing success were not statistically different between areas with and without wind energy development in the short-term. Nest success also was not influenced by anthropogenic features such as turbines in the short-term. Additionally, female survival was similar among both study areas, suggesting wind energy infrastructure was not impacting female survival in the short-term; however, further analysis is needed to identify habitats with different levels of risk to better understand the impact of wind energy development on survival. Nest and brood-rearing habitat selection were not influenced by turbines in the short-term; however, summer habitat selection occurred within habitats closer to wind turbines. Major roads were avoided in both study areas and during most of the seasons. The impact of transmission lines varied among study areas, suggesting other landscape features may be influencing selection. The data provided in this report are preliminary and are not meant to provide a basis for forming any conclusions regarding potential impacts of wind energy development on sage-grouse. Although the data collected during the initial phases of this study indicate that greater sage-grouse may continue to use habitats near wind-energy facilities, research conducted on greater sage-grouse response to oil and gas development has found population declines may not occur until 2-10 years after development. Therefore, long-term data from several geographic areas within the range of the sage-grouse will likely be required to adequately assess impacts of wind-energy development on greater sage-grouse.

17 WIND ENERGY↗
DOE OSTI2022

Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities

Nonparametric estimation for a probability density function that describes multivariate data has typically been addressed by kernel density estimation (KDE). A novel density estimator recently developed by Farmer and Jacobs offers an alternative high-throughput automated approach to univariate nonparametric density estimation based on maximum entropy and order statistics, improving accuracy over univariate KDE. This article presents an extension of the single variable case to multiple variables. The univariate estimator is used to recursively calculate a product array of one-dimensional conditional probabilities. In combination with interpolation methods, a complete joint probability density estimate is generated for multiple variables. Good accuracy and speed performance in synthetic data are demonstrated by a numerical study using known distributions over a range of sample sizes from 100 to 10 6 for two to six variables. Performance in terms of speed and accuracy is compared to KDE. The multivariate density estimate developed here tends to perform better as the number of samples and/or variables increases. As an example application, measurements are analyzed over five filters of photometric data from the Sloan Digital Sky Survey Data Release 17. The multivariate estimation is used to form the basis for a binary classifier that distinguishes quasars from galaxies and stars with up to 94% accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

System initial mass function of the 25 Ori group from planetary-mass objects to intermediate/high-mass stars

Abstract The stellar initial mass function (IMF) is an essential input for many astrophysical studies but only in a few cases has it been determined over the whole cluster mass range, limiting the conclusions about its nature. The 25 Orionis group (25 Ori) is an excellent laboratory for investigating the IMF across the entire mass range of the population, from planetary-mass objects to intermediate/high-mass stars. We combine new deep optical photometry with optical and near-infrared data from the literature to select 1687 member candidates covering a 1.1° radius area in 25 Ori. With this sample we derived the 25 Ori system IMF from 0.012 to 13.1 M⊙. This system IMF is well described by a two-segment power law with Γ = −0.74 ± 0.04 for m < 0.4 M⊙ and Γ = 1.50 ± 0.11 for m ≥ 0.4 M⊙. It is also well described over the whole mass range by a tapered power-law function with Γ = 1.10 ± 0.09, mp = 0.31 ± 0.03 and β = 2.11 ± 0.09. The best lognormal representation of the system IMF has mc = 0.31 ± 0.04 and σ = 0.46 ± 0.05 for m < 1 M⊙. This system IMF does not present significant variations with the radii. We compared the resultant system IMF as well as the brown dwarf/star ratio of 0.16 ± 0.03 that we estimated for 25 Ori with that of other stellar regions with diverse conditions and found no significant discrepancies. These results support the idea that general star-formation mechanisms are probably not strongly dependent on environmental conditions. We found that the substellar and stellar objects in 25 Ori do not have any preferential spatial distributions and confirmed that 25 Ori is a gravitationally unbound stellar association.

Suárez, Genaro↗
DOE OSTI2014

Are polynuclear superhalogens without halogen atoms probable? A high-level ab initio case study on triple-bridged binuclear anions with cyanide ligands

The first theoretical exploration of superhalogen properties of polynuclear structures based on pseudohalogen ligand is reported here via a case study on eight triply-bridged [Mg{sub 2}(CN){sub 5}]{sup −} clusters. From our high-level ab initio results, all these clusters are superhalogens due to their high vertical electron detachment energies (VDE), of which the largest value is 8.67 eV at coupled-cluster single double triple (CCSD(T)) level. Although outer valence Green's function results are consistent with CCSD(T) in most cases, it overestimates the VDEs of three anions dramatically by more than 1 eV. Therefore, the combined usage of several theoretical methods is important for the accuracy of purely theoretical prediction of superhalogen properties of new structures. Spatial distribution of the extra electron of high-VDE anions here indicates two features: remarkable aggregation on bridging CN units and non-negligible distribution on every CN unit. These two features lower the potential and kinetic energies of the extra electron respectively and thus lead to high VDE. Besides superhalogen properties, the structures, relative stabilities and thermodynamic stabilities with respect to detachment of CN{sup −1} were also investigated for these anions. The collection of these results indicates that polynuclear structures based on pseudohalogen ligand are promising candidates for new superhalogens with enhanced properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗