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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades

Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.

blade fatigue↗
NASA NTRS1979

Population statistics of faint stellar and non-stellar objects

A disc and halo population model is constructed to fit star counts and color data down to V approximately 23 at absolute value of b = 90 deg. This model is used to predict star counts and colors down to V approximately 30. Deviations from these extrapolated relationships provide constraints on the number of faint quasars and black dwarf stars. It is shown that extra-galactic globular clusters start contributing significantly to star counts at V approximately 25 and are more numerous than stars for V 31. Morphological studies of galaxies with approximately 0.5, were made with the space telescope. Significant constraints on theoretical models that describe the evolution of clusters of galaxies are provided.

Vandenbergh, S.↗
NASA NTRS1982

An inventory of undiscovered Canadian mineral resources

Unit regional value (URV) and unit regional weight are area standardized measures of the expected value and quantity, respectively, of the mineral resources of a region. Estimation and manipulation of the URV statistic is the basis of an approach to mineral resource evaluation. Estimates of the kind and value of exploitable mineral resources yet to be discovered in the provinces of Canada are used as an illustration of the procedure. The URV statistic is set within a previously developed model wherein geology, as measured by point counting geologic maps, is related to the historical record of mineral resource production of well-developed regions of the world, such as the 50 states of the U.S.A.; these may be considered the training set. The Canadian provinces are related to this training set using geological information obtained in the same way from geologic maps of the provinces. The desired predictions of yet to be discovered mineral resources in the Canadian provinces arise as a consequence. The implicit assumption is that regions of similar geology, if equally well developed, will produce similar weights and values of mineral resources.

Labovitz, M. L.↗
NASA NTRS1990

New bound on neutrino dipole moments from globular-cluster stars

Neutrino dipole moments mu(nu) would increase the core mass of red giants at the helium flash by delta(Mc) = 0.015 solar mass x mu(nu)/10 to the -12th muB (where muB is the Bohr magneton) because of enhanced neutrino losses. Existing measurements of the bolometric magnitudes of the brightest red giants in 26 globular clusters, number counts of horizontal-branch stars and red giants in 15 globular clusters, and statistical parallax determinations of field RR Lyr luminosities yield delta(Mc) = 0.009 + or - 0.012 solar mass, so that conservatively mu(nu) is less than 3 x 10 to the -12th muB.

Raffelt, Georg G.↗
DOE OSTI2020

Formulation and solution approach for calibrating activity-based travel demand model-system via microsimulation

This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibration of activity-based model-systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider the fundamental inter-dependencies among choice-models and do not have a systematic way to adjust model parameters. Also, other purely simulation-based approaches do not perform well in large-scale applications. In this study, we focus on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics such as activity shares, mode shares, time-dependent & mode-specific OD flows, and time-dependent & mode-specific sensor counts. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expectations of the aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function —that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model-system and is non-myopic in considering the dependencies across its model components. The formulated optimization problem is non-convex, highly nonlinear, and potentially has multiple-minima. Lastly, we show —through a real-world application— that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model-systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2002

Composition and physiological profiling of sprout-associated microbial communities

The native microfloras of various types of sprouts (alfalfa, clover, sunflower, mung bean, and broccoli sprouts) were examined to assess the relative effects of sprout type and inoculum factors (i.e., sprout-growing facility, seed lot, and inoculation with sprout-derived inocula) on the microbial community structure of sprouts. Sprouts were sonicated for 7 min or hand shaken with glass beads for 2 min to recover native microfloras from the surface, and the resulting suspensions were diluted and plated. The culturable fraction was characterized by the density (log CFU/g), richness (e.g., number of types of bacteria), and diversity (e.g., microbial richness and evenness) of colonies on tryptic soy agar plates incubated for 48 h at 30 degrees C. The relative similarity between sprout-associated microbial communities was assessed with the use of community-level physiological profiles (CLPPs) based on patterns of utilization of 95 separate carbon sources. Aerobic plate counts of 7.96 +/- 0.91 log CFU/g of sprout tissue (fresh weight) were observed, with no statistically significant differences in microbial cell density, richness, or diversity due to sprout type, sprout-growing facility, or seed lot. CLPP analyses revealed that the microbial communities associated with alfalfa and clover sprouts are more similar than those associated with the other sprout types tested. Variability among sprout types was more extensive than any differences between microbial communities associated with alfalfa and clover sprouts from different sprout-growing facilities and seed lots. These results indicate that the subsequent testing of biocontrol agents should focus on similar organisms for alfalfa and clover, but alternative types may be most suitable for the other sprout types tested. The inoculation of alfalfa sprouts with communities derived from various sprout types had a significant, source-independent effect on microbial community structure, indicating that the process of inoculation alters the dynamics of community development regardless of the types of organisms involved.

NASA Center KSC↗
DOE OSTI2019

Prediction of Transition-State Energies of Hydrodeoxygenation Reactions on Transition-Metal Surfaces Based on Machine Learning

Computational catalyst discovery involves identification of a meaningful model and suitable descriptors that determine the catalyst properties. We study the impact of combining various descriptors (e.g., reaction energies, metal descriptors, and bond counts) for modeling transition-state energies (TS) based on a database of adsorption and TS energies across transition-metal surfaces for the decarboxylation and decarbonylation of propionic acid, a chemistry characteristic for biomass conversion. Results of different machine learning models for more than 1572 descriptor combinations suggest that there is no statistically significant difference between linear and nonlinear models when using the right combination of reactant energies, metal descriptors, and bond counts. However, linear models are inferior when not including bond count and metal descriptors. In conclusion, when there are missing data for reaction steps on all metals, conventional linear scaling is inferior to linear and nonlinear models with proper choice of descriptors that are surprisingly robust.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Comparison of Infectious Disease Forecasting Methods across Locations, Diseases, and Time

Accurate infectious disease forecasting can inform efforts to prevent outbreaks and mitigate adverse impacts. This study compares the performance of statistical, machine learning (ML), and deep learning (DL) approaches in forecasting infectious disease incidences across different countries and time intervals. We forecasted three diverse diseases: campylobacteriosis, typhoid, and Q-fever, using a wide variety of features (n = 46) from public datasets, e.g., landscape, climate, and socioeconomic factors. We compared autoregressive statistical models to two tree-based ML models (extreme gradient boosted trees [XGB] and random forest [RF]) and two DL models (multi-layer perceptron and encoder–decoder model). The disease models were trained on data from seven different countries at the region-level between 2009–2017. Forecasting performance of all models was assessed using mean absolute error, root mean square error, and Poisson deviance across Australia, Israel, and the United States for the months of January through August of 2018. The overall model results were compared across diseases as well as various data splits, including country, regions with highest and lowest cases, and the forecasted months out (i.e., nowcasting, short-term, and long-term forecasting). Overall, the XGB models performed the best for all diseases and, in general, tree-based ML models performed the best when looking at data splits. There were a few instances where the statistical or DL models had minutely smaller error metrics for specific subsets of typhoid, which is a disease with very low case counts. Feature importance per disease was measured by using four tree-based ML models (i.e., XGB and RF with and without region name as a feature). The most important feature groups included previous case counts, region name, population counts and density, mortality causes of neonatal to under 5 years of age, sanitation factors, and elevation. This study demonstrates the power of ML approaches to incorporate a wide range of factors to forecast various diseases, regardless of location, more accurately than traditional statistical approaches.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Validation of Geant4’s G4NRF module against nuclear resonance fluorescence data from 238 U and 27 Al

G4NRF (Jordan and Warren, 2007; Vavrek et al., 2018a,b) is a simulation module for modeling nuclear resonance fluorescence (NRF) interactions in the Geant4 framework (Allison et al., 2016). In this work, we validate G4NRF against both absolute and relative measurements of three NRF interactions near 2.2 MeV in 238 U and 27 Al using the transmission NRF data from the experiments described in Jayson et al. (2018). Agreement between the absolute NRF count rates observed in the data and predicted by extensive Geant4+G4NRF modeling validate the combined Geant4+G4NRF to approximately 15–20% in the 238 U NRF transitions and 10% in 27 Al, for an average 14% discrepancy across the entire study. The difference between simulation and experiment in relative NRF rates, as expressed as ratios of count rates in various NRF lines, is found at the level of ≲3%, and is statistically identical to zero. Finally, inverting the analysis, approximate values of the absolute level widths and branching ratios for 238 U and 27 Al are also obtained.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Assessing Historical Variability of South Asian Monsoon Lows and Depressions With an Optimized Tracking Algorithm

Abstract Cyclonic low‐pressure systems (LPS) produce abundant rainfall in South Asia, where they are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department (IMD) has tracked monsoon depressions for over a century, finding a large decline in their number in recent decades, but their methods have changed over time and do not include monsoon lows. This study presents a fast, objective algorithm for identifying monsoon LPS and uses it to assess interannual variability and trends in reanalyses. Variables and thresholds used in the algorithm are selected to best match a subjectively analyzed LPS data set while minimizing disagreement between four reanalyses in a training period. The stream function of 850 hPa horizontal wind is found to be optimal in this sense; it is less noisy than vorticity and represents the complete nondivergent wind, even when flow is not geostrophic. Using this algorithm, LPS statistics are computed for five reanalyses, and none show a detectable trend in monsoon depression counts since 1979. Both the Japanese 55‐year Reanalysis (JRA‐55) and the IMD data set show a step‐like reduction in depression counts when they began using geostationary satellite data, in 1979 and 1982, respectively; the 1958–2018 linear trend in JRA‐55, however, is smaller than in the IMD data set, and its error bar includes 0. There are more LPS in seasons with above‐average monsoon rainfall and in La Niña years, but few other large‐scale modes of interannual variability are found to modulate LPS counts, lifetimes, or track length consistently across reanalyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Maxwell–Boltzmann statistics of the quantum ideal gas in the canonical ensemble

Abstract The Maxwell–Boltzmann statistics of the quantum ideal gas is studied through the canonical partition function by exactly counting discrete quantum states without the continuum approximation. Analytic expressions for energy, pressure, entropy, and heat capacity are expressed in terms of Jacobi theta functions and complete elliptic integrals. The results show typical effects of discrete energy levels in the low temperature limit while they reproduce thermodynamics of the classical ideal gas in the high temperature limit.

Mechanics↗
NASA NTRS1979

A study of solar flare electron events from October 1972 through December 1974 from Imp 7 and 8

Data from the Johns Hopkins University Applied Physics Laboratory Charged Particle Measurement Experiment aboard Imp H and J were searched for solar flare produced intensity increases in greater than 0.2-MeV electrons during the 26-month period from October 1972 through December 1974. Of the 44 solar electron events found during this period, 31 were isolated for a detailed statistical study. Systematics among the characteristics of the electron profiles (e.g., peak intensity times and count rates) and those of the associated flares (e.g., H-alpha onset times, H-alpha importance class, heliocentric coordinates, etc.) were examined, and the significant results are presented in several scatter plots. The results reveal that the time delay between the flare onset and the arrival of the peak electron intensity at 1 AU (time to maximum) is a function of the flare's deviation in heliolongitude from the solar region which was well connected to the earth via a magnetic flux tube; the well-connected flares produced electron intensity maxima in the least time.

Decker, R. B.↗
NASA NTRS2010

Global Patterns of Lightning Properties Derived by LIS

The Lightning Imaging Sensor LIS aboard the TRMM satellite provides unmatched empirical data of the global lightning distribution (up to approx.35deg S/N) since end of 1997. Climatological flash rate densities derived from LIS are standard references, e.g. for flash rate parameterizations used in GCMs. It is known that flash characteristics are quite variable, and that various quantities (like the flash energy or the NOx production per flash) vary considerably, statistically as well as systematically on regional and seasonal scales. LIS provides information beyond flash counts, in particular radiance and flash footprint. Here we present an analysis of global patterns of various lightning properties derived from LIS, in relation to the number of flashes. These normalized flash characteristics show consistent spatial patterns of regions with "strong" versus regions with "weak" lightning. Most striking is a clear land-ocean contrast, with oceanic flashes being "stronger" than continental flashes. But also over continents, flash strength shows systematic variations. Highest continental values are found over the US, while values over South America and India are quite low. These regional variations cannot be simply parameterized as function of latitude. Information on spatial patterns of mean flash "strength", though rather qualitative up to now, is potentially a valuable input for improving empirical parameterizations based on flash counts (like precipitation or lightning NOx). Further investigation is in progress to come to a more physical and quantitative understanding of the spatial patterns of the different LIS properties. In particular, it has to be checked how far they could be related to established lightning properties (like energy or the fraction of intra-cloud to cloud-to-ground flashes) or to meteorological quantities (like CAPE).

Beirle, S.↗
NASA NTRS2011

On the Sensitivity of the HAWC Observatory to Gamma-Ray Bursts

We present the sensitivity of HAWC to Gamma Ray Bursts (GRBs). HAWC is a very high-energy gamma-ray observatory currently under construction in Mexico at an altitude of 4100 m. It will observe atmospheric air showers via the water Cherenkov method. HAWC will consist of 300 large water tanks instrumented with 4 photomultipliers each. HAWC has two data acquisition (DAQ) systems. The main DAQ system reads out coincident signals in the tanks and reconstructs the direction and energy of individual atmospheric showers. The scaler DAQ counts the hits in each photomultiplier tube (PMT) in the detector and searches for a statistical excess over the noise of all PMTs. We show that HAWC has a realistic opportunity to observe the high-energy power law components of GRBs that extend at least up to 30 GeV, as it has been observed by Fermi LAT. The two DAQ systems have an energy threshold that is low enough to observe events similar to GRB 090510 and GRB 090902b with the characteristics observed by Fermi LAT. HAWC will provide information about the high-energy spectra of GRBs which in turn will lead to understanding about e-pair attenuation in GRB jets, extragalactic background light absorption, as well as establishing the highest energy to which GRBs accelerate particles.

Hays, E.↗
DOE OSTI2024

Relative State Counting for Semiclassical Black Holes

It has been shown that entropy differences between certain states of perturbative quantum gravity can be computed without specifying an ultraviolet completion. This is analogous to the situation in classical statistical mechanics, where entropy differences are defined but absolute entropy is not. Unlike in classical statistical mechanics, however, the entropy differences computed in perturbative quantum gravity do not have a clear physical interpretation. Here we construct a family of perturbative black hole states for which the entropy difference can be interpreted as a relative counting of states. Conceptually, this Letter begins with the algebra of mass fluctuations around a fixed black hole background, and points out that while this is a type I algebra, it is not a factor and therefore has no canonical definition of entropy. As in previous work, coupling the mass fluctuations to quantum matter embeds the mass algebra within a type II factor, in which entropy differences (but not absolute entropies) are well defined. It is then shown that for microcanonical wave functions of mass fluctuation, the type II entropy difference equals the logarithm of the dimension of the extra Hilbert space that is needed to map one microcanonical window to another using gauge-invariant unitaries. The Letter closes with comments on type II entropy difference in a more general class of states, where the von Neumann entropy difference does not have a physical interpretation, but “one-shot” entropy differences do. Published by the American Physical Society 2024

Akers, Chris (ORCID:0000000227929827)↗
NASA NTRS1986

Detection of large-scale alignment of Lick counts around Abell clusters

The possible tendency of galaxies to be distributed in an aligned fashion, on sheets or filaments, on scales greater than the Abell radius, has been tested by a variety of statistics. The subject remains controversial because the statistical tests have either not been sensitive to the alignment or capable of unambiguously signalling alignment in a general, clumpy distribution of galaxies. The present approach combines ideas of Bingelli (1982) and Fry and Peebles (1980) in an examination of the cross correlation of Lick counts relative to the preferred direction defined by the cluster. This can substantially reduce the noise, and it is suggested on this basis that alignment has been found on large scales for Lick galaxy counts and Abell cluster positions and their angles.

Argyres, P. C.↗
DOE OSTI2024

Cosmology from weak lensing peaks and minima with Subaru Hyper Suprime-Cam Survey first-year data

We present cosmological constraints derived from peak counts, minimum counts, and the angular power spectrum of the Subaru Hyper Suprime-Cam first-year (HSC Y1) weak lensing shear catalogue. Weak lensing peak and minimum counts contain non-Gaussian information and hence are complementary to the conventional two-point statistics in constraining cosmology. In this work, we forward-model the three summary statistics and their dependence on cosmology, using a suite of N-body simulations tailored to the HSC Y1 data. We investigate systematic and astrophysical effects including intrinsic alignments, baryon feedback, multiplicative bias, and photometric redshift uncertainties. We mitigate the impact of these systematics by applying cuts on angular scales, smoothing scales, signal-to-noise ratio bins, and tomographic redshift bins. By combining peaks, minima, and the power spectrum, assuming a flat-ΛCDM model, we obtain S 8 ≡ σ 8 $\sqrt{Ω_m/0.3}$ = 0.810$^{+0.022}_{-0.026}$⁠, a 35 per cent tighter constraint than that obtained from the angular power spectrum alone. Our results are in agreement with other studies using HSC weak lensing shear data, as well as with Planck 2018 cosmology and recent CMB lensing constraints from the Atacama Cosmology Telescope and the South Pole Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗