Observation of muon intensity variations by season with the MINOS near detector
N/A
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
SEARCH · Engineering Papers
Results for “Function Estimation”
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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Dark Energy Survey year 6 results: Magnification modeling and its impact on galaxy clustering and galaxy-galaxy lensing cosmology
Gravitational lensing magnification alters the observed spatial distribution of galaxies and must be accounted for to prevent biases in cosmological probes of the large-scale structure. We investigate its effects on the Dark Energy Survey Year 6 galaxy clustering and galaxy-galaxy lensing analyses using the fiducial lens (position tracer) sample M ag L im++. Magnification bias is parameterized by a coefficient that describes the response of the number of selected objects per unlensed area element to a change in the lensing convergence. We quantify this coefficient using the BALROG synthetic source injection catalog to account for the complexity of the selection function, and compare these results with simplified estimates. The resulting values of the magnification coefficients for each redshift bin are [3.16 ± 0.08, 2.76 ± 0.21, 4.09 ± 0.15, 4.42 ± 0.16, 4.90 ± 0.29, 4.83 ± 0.25]. Relative to Year 3, this analysis provides more precise and accurate magnification bias estimates through a larger BALROG area and reweighting to better match the data properties. Here, the cosmological results are robust when tested against various magnification parameter prior choices and also when adding cross-clustering between lens redshift bins. Neglecting magnification, however, introduces significant systematic shifts: relative to the fiducial analysis with Gaussian priors centered on the BALROG -derived estimates, we observe shifts of 1.37σ in S 8 and -0.84σ in Ω m (with cosmic shear included: -0.61σ in S 8 and -0.71σ in Ω m ), in agreement with findings from simulated data, demonstrating that magnification must be modeled to avoid biases. Freeing the magnification bias in lens bin 2 leads to unphysical negative values, further justifying its exclusion from the fiducial Year 6 analysis.
Cosmological parameters↗
Molybdenum oxide and molybdenum oxide-nitride back contacts for CdTe solar cells
Molybdenum oxide (MoO{sub x}) and molybdenum oxynitride (MoON) thin film back contacts were formed by a unique ion-beam sputtering and ion-beam-assisted deposition process onto CdTe solar cells and compared to back contacts made using carbon–nickel (C/Ni) paint. Glancing-incidence x-ray diffraction and x-ray photoelectron spectroscopy measurements show that partially crystalline MoO{sub x} films are created with a mixture of Mo, MoO{sub 2}, and MoO{sub 3} components. Lower crystallinity content is observed in the MoON films, with an additional component of molybdenum nitride present. Three different film thicknesses of MoO{sub x} and MoON were investigated that were capped in situ in Ni. Small area devices were delineated and characterized using current–voltage (J-V), capacitance–frequency, capacitance–voltage, electroluminescence, and light beam-induced current techniques. In addition, J-V data measured as a function of temperature (JVT) were used to estimate back barrier heights for each thickness of MoO{sub x} and MoON and for the C/Ni paint. Characterization prior to stressing indicated the devices were similar in performance. Characterization after stress testing indicated little change to cells with 120 and 180-nm thick MoO{sub x} and MoON films. However, moderate-to-large cell degradation was observed for 60-nm thick MoO{sub x} and MoON films and for C/Ni painted back contacts.
14 SOLAR ENERGY↗
TH-AB-202-12: The First Clinical Implementation of a Real-Time Six Degree of Freedom Tracking System During Radiation Therapy
Purpose: In current practice, imaging is typically performed prior to treatment; the cancer target motion during treatment is unknown. We present the first clinical implementation of real time Kilovoltage Intrafraction Monitoring (KIM) system which tracks the cancer target translational and rotational motions during treatment. Methods: KIM technology: KIM estimates the 3D position of the target tumour based on segmented 2D positions of the three implanted fiducials in each of the kV images (125 kV, 10 mA at 11 fps) taken continuously during the treatment arc. The 2D-3D target estimation is based on a probability distribution function, obtained during pre-treatment CBCT. Rotations about each axis with the centroid of the markers as the pivot were calculated using the iterative closest point algorithm in real time. Patient: A patient with prostate adenocarcinoma undergoing stereotactic body radiotherapy (SBRT) with 36.25 Gy delivered in 5 fractions (Varian TrueBeam, 6X, VMAT) was enrolled in the study. The trial complies with Australian ethical and regulatory standards. Results: Of the 5 fractions of treatment the patient received, KIM was utilised successfully in 4 fractions with 3 couch shifts due to large persistent prostate movements (>2mm for more than 5 seconds). KIM translational accuracy and precision in comparison with post treatment kV-MV triangulation are 0.28±0.59 mm, −0.19±0.25 mm and 0.23±0.69 mm in the Left-Right, Superior-Inferior and Anterior-Posterior directions, respectively. KIM rotational accuracy as compared with triangulation is: 0.429°±2.22°, −0.44°±4.7° and 0.06°±1.08° in the roll, pitch and yaw direction, respectively. Conclusion: The first six degree of freedom KIM system was successfully implemented clinically. The presented KIM system has sub-millimeters accuracy and precision in all three translational axes, and less than 1° of mean error in all three rotational axes. Acknowledgement: This work is supported by Cancer Australia grants APPXXX, APPYYY.
60 APPLIED LIFE SCIENCES↗
Genome Sizes and the Benford Distribution
Background: Data on the number of Open Reading Frames (ORFs) coded by genomes from the 3 domains of Life show the presence of some notable general features. These include essential differences between the Prokaryotes and Eukaryotes, with the number of ORFs growing linearly with total genome size for the former, but only logarithmically for the latter. Results: Simply by assuming that the (protein) coding and non-coding fractions of the genome must have different dynamics and that the non-coding fraction must be particularly versatile and therefore be controlled by a variety of (unspecified) probability distribution functions (pdf’s), we are able to predict that the number of ORFs for Eukaryotes follows a Benford distribution and must therefore have a specific logarithmic form. Using the data for the 1000+ genomes available to us in early 2010, we find that the Benford distribution provides excellent fits to the data over several orders of magnitude. Conclusions: In its linear regime the Benford distribution produces excellent fits to the Prokaryote data, while the full nonlinear form of the distribution similarly provides an excellent fit to the Eukaryote data. Furthermore, in their region of overlap the salient features are statistically congruent. This allows us to interpret the difference between Prokaryotes and Eukaryotes as the manifestation of the increased demand in the biological functions required for the larger Eukaryotes, to estimate some minimal genome sizes, and to predict a maximal Prokaryote genome size on the order of 8–12 megabase pairs. These results naturally allow a mathematical interpretation in terms of maximal entropy and, therefore, most efficient information transmission.
54 ENVIRONMENTAL SCIENCES↗
Universality of phase transition dynamics: topological defects from symmetry breaking
In the course of a non-equilibrium continuous phase transition, the dynamics ceases to be adiabatic in the vicinity of the critical point as a result of the critical slowing down (the divergence of the relaxation time in the neighborhood of the critical point). This enforces a local choice of the broken symmetry and can lead to the formation of topological defects. The Kibble-Zurek mechanism (KZM) was developed to describe the associated nonequilibrium dynamics and to estimate the density of defects as a function of the quench rate through the transition. During recent years, several new experiments investigating formation of defects in phase transitions induced by a quench both in classical and quantum mechanical systems were carried out. At the same time, some established results were called into question. We review and analyze the Kibble-Zurek mechanism focusing in particular on this surge of activity, and suggest possible directions for further progress.
74 ATOMIC AND MOLECULAR PHYSICS↗
Statistical Hot Channel Analysis for the NBSR
A statistical analysis of thermal limits has been carried out for the research reactor (NBSR) at the National Institute of Standards and Technology (NIST). The objective of this analysis was to update the uncertainties of the hot channel factors with respect to previous analysis for both high-enriched uranium (HEU) and low-enriched uranium (LEU) fuels. Although uncertainties in key parameters which enter into the analysis are not yet known for the LEU core, the current analysis uses reasonable approximations instead of conservative estimates based on HEU values. Cumulative distribution functions (CDFs) were obtained for critical heat flux ratio (CHFR), and onset of flow instability ratio (OFIR). As was done previously, the Sudo-Kaminaga correlation was used for CHF and the Saha-Zuber correlation was used for OFI. Results were obtained for probability levels of 90%, 95%, and 99.9%. As an example of the analysis, the results for both the existing reactor with HEU fuel and the LEU core show that CHFR would have to be above 1.39 to assure with 95% probability that there is no CHF. For the OFIR, the results show that the ratio should be above 1.40 to assure with a 95% probability that OFI is not reached.
42 ENGINEERING↗
An Elastic Plastic Contact Model with Strain Hardening for the LAMMPS Granular Package
The following details the implementation of an analytical elastic plastic contact model with strain hardening for normal im pacts into the LAMMPS granular package. The model assumes that, upon impact, the co llision has a period of elastic loading followed by a period of mixed elastic plas tic loading, with contributions to each mechanism estimated by a hyperbolic seca nt weight function. This function is implemented in the LAMMPS source code as the pair style gran/ep/history. Preliminary tests, simulating the pouring of pure nickel spheres, showed the elastic/plastic model took 1.66x as long as similar runs using gran/hertz/history.
36 MATERIALS SCIENCE↗
New approaches for understanding the statistics of daily weather extremes in a changing climate. SARDESHMUKH_Final_Technical_Report_Extremes_DE-SC0006965
This project quantified the changes in the mean climate and climate variability over the last 140 years, with emphasis on the changes in the tails of the probability distributions of daily variations, i.e. changes in extreme weather statistics. We were interested in not just the mean shifts of the distributions under climate change but also changes in the variance and higher statistical moments such as skewness and kurtosis. The project focused on two important aspects of the probability density functions (pdfs) of daily anomalies and their estimations from observational records of limited length. The first is that the pdfs are not Gaussian but are distinctively skewed and heavy tailed. This has large implications for the probabilities of extreme values and for estimating those probabilities from limited records. It also motivated our second focus, to estimate the pdfs from the longest available global datasets based on instrumental observations.
54 ENVIRONMENTAL SCIENCES↗
Efficient First-Order Algorithms for Large-Scale, Non-Smooth Maximum Entropy Models with Application to Wildfire Science
Maximum entropy (MaxEnt) models are a class of statistical models that use the maximum entropy principle to estimate probability distributions from data. Due to the size of modern data sets, MaxEnt models need efficient optimization algorithms to scale well for big data applications. State-of-the-art algorithms for MaxEnt models, however, were not originally designed to handle big data sets; these algorithms either rely on technical devices that may yield unreliable numerical results, scale poorly, or require smoothness assumptions that many practical MaxEnt models lack. In this paper, we present novel optimization algorithms that overcome the shortcomings of state-of-the-art algorithms for training large-scale, non-smooth MaxEnt models. Our proposed first-order algorithms leverage the Kullback–Leibler divergence to train large-scale and non-smooth MaxEnt models efficiently. For MaxEnt models with discrete probability distribution of n elements built from samples, each containing m features, the stepsize parameter estimation and iterations in our algorithms scale on the order of O(mn) operations and can be trivially parallelized. Moreover, the strong ℓ1 convexity of the Kullback–Leibler divergence allows for larger stepsize parameters, thereby speeding up the convergence rate of our algorithms. To illustrate the efficiency of our novel algorithms, we consider the problem of estimating probabilities of fire occurrences as a function of ecological features in the Western US MTBS-Interagency wildfire data set. Our numerical results show that our algorithms outperform the state of the art by one order of magnitude and yield results that agree with physical models of wildfire occurrence and previous statistical analyses of wildfire drivers.
Physics↗
The SFR–M{sub *} relation and empirical star formation histories from ZFOURGE at 0.5 < z < 4
We explore star formation histories (SFHs) of galaxies based on the evolution of the star formation rate stellar mass relation (SFR–M{sub *}). Using data from the FourStar Galaxy Evolution Survey (ZFOURGE) in combination with far-IR imaging from the Spitzer and Herschel observatories we measure the SFR–M{sub *} relation at 0.5 < z < 4. Similar to recent works we find that the average infrared spectral energy distributions of galaxies are roughly consistent with a single infrared template across a broad range of redshifts and stellar masses, with evidence for only weak deviations. We find that the SFR–M{sub *} relation is not consistent with a single power law of the form SFR∝M{sub ∗}{sup α} at any redshift; it has a power law slope of α ∼ 1 at low masses, and becomes shallower above a turnover mass (M{sub 0}) that ranges from 10{sup 9.5} to 10{sup 10.8} M{sub ⊙}, with evidence that M{sub 0} increases with redshift. We compare our measurements to results from state-of-the-art cosmological simulations, and find general agreement in the slope of the SFR–M{sub *} relation albeit with systematic offsets. We use the evolving SFR–M{sub *} sequence to generate SFHs, finding that typical SFRs of individual galaxies rise at early times and decline after reaching a peak. This peak occurs earlier for more massive galaxies. We integrate these SFHs to generate mass growth histories and compare to the implied mass growth from the evolution of the stellar mass function (SMF). We find that these two estimates are in broad qualitative agreement, but that there is room for improvement at a more detailed level. At early times the SFHs suggest mass growth rates that are as much as 10× higher than inferred from the SMF. However, at later times the SFHs under-predict the inferred evolution, as is expected in the case of additional growth due to mergers.
79 ASTRONOMY AND ASTROPHYSICS↗
Detection and Interpretation of Long-lived X-Ray Quasi-periodic Pulsations in the X-class Solar Flare on 2013 May 14
Quasi-periodic pulsations (QPP) seen in the time derivative of the GOES soft X-ray light curves are analyzed for the X3.2 event on 2013 May 14. The pulsations are apparent for a total of at least two hours from the impulsive phase to well into the decay phase, with a total of 163 distinct pulses evident to the naked eye. A wavelet analysis shows that the characteristic timescale of these pulsations increases systematically from ∼25 s at 01:10 UT, the time of the GOES peak, to ∼100 s at 02:00 UT. A second “ridge” in the wavelet power spectrum, most likely associated with flaring emission from a different active region, shows an increase from ∼40 s at 01:40 UT to ∼100 s at 03:10 UT. We assume that the QPP that produced the first ridge result from vertical kink-mode oscillations of the newly formed loops following magnetic reconnection in the coronal current sheet. This allows us to estimate the magnetic field strength as a function of altitude given the density, loop length, and QPP timescale as functions of time determined from the GOES light curves and Ramaty High Energy Solar Spectroscopic Imager ( RHESSI ) images. The calculated magnetic field strength of the newly formed loops ranges from ∼500 G at an altitude of 24 Mm to a low value of ∼10 G at 60 Mm, in general agreement with the expected values at these altitudes. Fast sausage-mode oscillations are also discussed and cannot be ruled out as an alternate mechanism for producing the QPP.
79 ASTRONOMY AND ASTROPHYSICS↗
Search for Gravitational-wave Signals Associated with Gamma-Ray Bursts during the Second Observing Run of Advanced LIGO and Advanced Virgo
We present the results of targeted searches for gravitational-wave transients associated with gamma-ray bursts during the second observing run of Advanced LIGO and Advanced Virgo, which took place from 2016 November to 2017 August. We have analyzed 98 gamma-ray bursts using an unmodeled search method that searches for generic transient gravitational waves and 42 with a modeled search method that targets compact-binary mergers as progenitors of short gamma-ray bursts. Both methods clearly detect the previously reported binary merger signal GW170817, with p-values of <9.38 10 -6 (modeled) and 3.1 10 -4 (unmodeled). We do not find any significant evidence for gravitational-wave signals associated with the other gamma-ray bursts analyzed, and therefore we report lower bounds on the distance to each of these, assuming various source types and signal morphologies. Using our final modeled search results, short gamma-ray burst observations, and assuming binary neutron star progenitors, we place bounds on the rate of short gamma-ray bursts as a function of redshift for z ≤ 1. We estimate 0.07-1.80 joint detections with Fermi-GBM per year for the 2019-20 LIGO-Virgo observing run and 0.15-3.90 per year when current gravitational-wave detectors are operating at their design sensitivities.
79 ASTRONOMY AND ASTROPHYSICS↗
A rich globular cluster system in dragonfly 17: are ultra-diffuse galaxies pure stellar halos?
Observations of nearby galaxy clusters at low surface brightness have identified galaxies with low luminosities, but sizes as large as L {sup ⋆} galaxies, leading them to be dubbed “ultra-diffuse galaxies” (UDGs). The survival of UDGs in dense environments like the Coma cluster suggests that UDGs could reside in much more massive dark halos. We report the detection of a substantial population of globular clusters (GCs) around a Coma UDG, Dragonfly 17 (DF17). We find that DF17 has a high GC specific frequency of S {sub N} = 26 ± 13. The GC system is extended, with an effective radius of 12″ ± 2″, or 5.6 ± 0.9 kpc at Coma distance, 70% larger than the galaxy itself. We also estimate the mean of the GC luminosity function to infer a distance of 97{sub −14}{sup +17} Mpc, providing redshift-independent confirmation that one of these UDGs is in the Coma cluster. The presence of a rich GC system in DF17 indicates that, despite its low stellar density, star formation was intense enough to form many massive star clusters. If DF17's ratio of total GC mass to total halo mass is similar to those in other galaxies, then DF17 has an inferred total mass of ∼10{sup 11} M {sub ⊙}, only ∼10% the mass of the Milky Way, but extremely dominated by dark matter, with M/L {sub V} ≈ 1000. We suggest that UDGs like DF17 may be “pure stellar halos,” i.e., galaxies that formed their stellar halo components, but then suffered an early cessation in star formation that prevented the formation of any substantial central disk or bulge.
79 ASTRONOMY AND ASTROPHYSICS↗
Shrub Seedling Experiment: Environmental Conditions, Vegetation Composition, and Seedling Recruitment, Seward Peninsula, Alaska, 2018-2019
In June 2018, a manipulative seed-addition experiment was established at the Council Mile Marker 71 (CN_MM71), Quartz Creek Burn Area (Kougarok Mile Marker 86), and Quartz Creek Unburned (Kougarok Mile Marker 80) sites on the Seward Peninsula, Alaska. At each site, 5 replicate blocks were established in disturbed and intact upland tussock tundra (a total of 40 plots). Disturbed plots at Council were located on thermo-erosional (thermokarst) slopes, while disturbed plots in Quartz Creek were in burned areas affected by the Mingvk Lake fire in 2015. Using a split-plot design, an additional manual disturbance treatment (scraping to remove the surface bryophyte layer) was implemented across all blocks in June 2018. Seeds of five erect, deciduous shrubs were broadcast seeded into each plot in June 2018, and seedlings were censused in August 2018 and August 2019. The dataset includes ancillary measurements of plot-level environmental conditions (soil temperature, moisture, chemistry, thaw depth, microtopography, substrate thickness) and vegetation composition (NDVI and estimated percent cover by species and plant functional type). Dataset contains 10 csv data files (five data files with corresponding data dictionaries and one file-level metadata file) and one pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
Diffusion velocity correlation for nuclear graphite gasification at high temperature and low Reynolds numbers
The safety analysis of High-Temperature and Very High Temperature gas-cooled Reactors requires reliable estimates of nuclear graphite gasification as a function of temperature, among other parameters, in the unlikely event of an air ingress accident. Although the rates of the prevailing chemical reactions increase exponentially with temperature, graphite gasification at high temperatures is limited by the oxygen diffusion through the boundary layer. The effective diffusion velocity depends on the total flow rate and pressure of the bulk air-gas mixture. This paper develops a semi-empirical Sherwood number correlation for calculating the oxygen diffusion velocity. The correlation is based on a compiled database of the results of convective heat transfer experiments with wires and cylinders of different diameters in air, water and paraffin oil at 0.006 {<=} Re {<=} 1,604 and 0.068 {<=} Sc {<=} 35.2, and of mass transfer experiments at 4.8 {<=} Re {<=} 77 and 1,300 {<=} Sc {<=} 2,000. The developed correlation is within {+-} 8% of the compiled database of 567 data points and consistent with reported gasification rate measurements at higher temperatures in experiments using different size specimens of nuclear graphite grades of NBG-18 and NB-25, IG-11, IG-110 and IG-430 in atmospheric air at 0.08 {<=} Re {<=} 30. Unlike the Graetz solution that gives a constant Sh of 3.66 at Re {<=} 1.0, the present correlation shows Sh decreases monotonically to much lower values with decreasing Re. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Analysis of Waste Material Feedstocks Using Laser-Induced Breakdown Spectroscopy and Machine Learning
Predicting properties such as heating value, ash fusion temperature, and mineral ash composition from Laser-Induced Breakdown Spectroscopy (LIBS) data can make gasifiers more flexible to different feedstocks. Understanding these feedstock properties in-situ improves feedstock conversion modelling methods that allow for consistent operation, higher carbon conversion, and reduced fouling and erosion rates. The purpose of this study is to demonstrate methods for model creation that take LIBS data as predictor features and estimate higher order material properties as a function of feedstock material properties. Six samples were chosen to represent a mixture of abundant and carbon rich waste materials. LIBS measurements were performed on these samples for elemental wavelengths and intensity values. Laboratory analytical results were obtained for each sample’s heating value, proximate and ultimate analysis, mineral ash composition, ash fusion temperatures, and viscosity temperatures. Thermal conductivity was measured using a HotDisk TPS 2500S. LIBS measurements were processed and used as predictor features for machine learning (ML) models to predict the sample’s material properties. Predictor feature selection algorithms, particularly minimum redundancy maximum relevance (mRMR), reduced the dimensionality of ML models. Many modelling methods such as Gaussian process regression (GPR), regression tree, neural networks (NN), and support vector machines (SVM) were demonstrated to be effective at predicting higher order properties; however, mRMR with GPR stood out as a clear winning combination.
01 COAL, LIGNITE, AND PEAT↗
Model independent x-ray standing wave analysis of periodic multilayer structures
We present a model independent approach for the analysis of X-ray fluorescence yield modulated by an X-ray standing wave (XSW), that allow a fast reconstruction of the atomic distribution function inside a sample without fitting procedure. The approach is based on the direct regularized solution of the system of linear equations that characterizes the fluorescence yield. The suggested technique was optimized for, but not limited to, the analysis of periodic layered structures where the XSW is formed under Bragg conditions. The developed approach was applied to the reconstruction of the atomic distribution function for LaN/BN multilayers with 50 periods of 43 Å thick layers. The object is especially difficult to analyze with traditional methods, as the estimated thickness of the interface region between the constituent materials is comparable to the individual layer thicknesses. However, using the suggested technique, it was possible to reconstruct width of the La atomic distribution showing that the La atoms stay localized within the LaN layers and interfaces and do not diffuse into the BN layer. The analysis of the reconstructed profiles showed that the positions of the center of the atomic distribution function can be estimated with an accuracy of 1 Å.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗