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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Progressing Analysis of Variable Electric Rates (PAVER) Study

The Progressing Analysis of Variable Electric Rates (PAVER) study analyzed the impact of a range of time-varying electric rates on the performance of a regional electric grid and the resulting costs for participating and non-participating customers. This analysis leveraged and extended the work of PNNL’s Distribution System Operator with Transactive (DSO+T) study. Five different rate designs were included: a flat volumetric energy charge, a typical Time of Use (TOU) rate, a dynamic energy (DE) rate (based on wholesale locational marginal prices), a dynamic energy and capacity (DE+C) rate, and, finally, a Block and Swing (B&S) rate that billed customers based on their average load profile at constant pricing, but used the DE+C dynamic price for load deviations from their average profile. These rates were analyzed in a large-scale co-simulation of an entire regional grid with a customer population representative of the current state. A large fraction (80%) of residential and commercial customers were assumed to participate in these time-varying rates with automatically controlled HVAC, water heaters, electric vehicles, and batteries. This study assumed no industrial sector participation. The DE and DE+C rates saw system peak loads reduced by 6-7%, while the large participation in the TOU rate case saw a significant rebound effect and a resulting peak load increase of >5%. The impacts to the annual and peak system demand impacted system wholesale prices and the overall grid operating costs. This cost structure determined the revenue needed to be collected from customers by each rate design. Participating customers on the DE and DE+C rates (located in one of the modeled DSOs) saw reductions in average annual electricity bills of 11-17% with average increases in monthly bill variation of no more than 13%. At such high participation levels, TOU customers saw 10% higher average annual bills (due to system-wide rebound effects) and average increased monthly bill variation of 16%. Residential owners of large flexible loads (such as electric vehicles) saw larger bill savings (17-20%) when on a fully dynamic rate. The presence of on-site generation (such as rooftop solar) did not appear to appreciably change customer outcomes. Customers on the Block and Swing rate did see 6% lower monthly bill variation (as intended) than the flat rate case, but at the expense of appreciable bill savings, which were only 3%, comparable to the savings seen by non-participants. Given this finding we recommend that additional research be conducted into how best various bill protection mechanisms can balance minimizing customer bill variation with providing financial incentives commensurate with the flexibility customers provide. We also recommend that customer outcomes be explored across a range of regions using current actual customer and system cost data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

A Closure Study of Total Scattering Using Airborne In Situ Measurements from the Winter Phase of TCAP

We examine the performance of our approach for calculating the total scattering coefficient of both non-absorbing and absorbing aerosol at ambient conditions from aircraft data. Our extended examination involves airborne in situ data collected by the U.S. Department of Energy’s (DOE) Gulf Stream 1 aircraft during winter over Cape Cod and the western North Atlantic Ocean as part of the Two-Column Aerosol Project (TCAP). The particle population represented by the winter dataset, in contrast with its summer counterpart, contains more hygroscopic particles and particles with an enhanced ability to absorb sunlight due to the larger fraction of black carbon. Moreover, the winter observations are characterized by more frequent clouds and a larger fraction of super-micron particles. We calculate model total scattering coefficient at ambient conditions using size spectra measured by optical particle counters (OPCs) and ambient complex refractive index (RI) estimated from measured chemical composition and relative humidity (RH). We demonstrate that reasonable agreement (~20% on average) between the observed and calculated scattering can be obtained under subsaturated ambient conditions (RH < 80%) by applying both screening for clouds and chemical composition data for the RI-based correction of the OPC-derived size spectra.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Electrical capacitance as a predictor of root dry weight in shrub willow ( Salix ; Salicaceae) parents and progeny

Premise of the study: Root biomass is an important trait often disregarded in woody perennial selection due to the challenge and expense of accurately and efficiently measuring large populations. In this study, we aim to develop a simple method that can predict root dry weight within a diverse shrub willow ( Salix ) breeding population representing species hybrids and their parents using root electrical capacitance (REC). Methods: The REC method was tested on plants started from cuttings and grown in pots with potting mix in the greenhouse for 11 wk to assess the relationship of REC with 24 biomass traits and its usefulness in allometric models for root and stem dry biomass. Results: Strong linear and positive correlations were found between REC and root dry biomass ( r = 0.88). The total proportion of variance of root and stem dry biomass explained by predictors in multiple regression was 85% and 69%, respectively. The relative importance of predictor variables in allometric models was dominated by the contribution of REC. Discussion: This work provides an efficient and nondestructive technique to indirectly quantify root biomass of genetically diverse shrub willow progeny, which has great promise for selection of genotypes with varying root biomass and for the accurate estimation of belowground carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

CHARACTERIZING THE POPULATION OF BRIGHT INFRARED SOURCES IN THE SMALL MAGELLANIC CLOUD

We have used the Infrared Spectrograph (IRS) on the Spitzer Space Telescope to observe stars in the Small Magellanic Cloud (SMC) selected from the Point Source Catalog of the Midcourse Space Experiment (MSX). We concentrate on the dust properties of the oxygen-rich evolved stars. The dust composition has smaller contributions from alumina compared to the Galaxy. This difference may arise from the lower metallicity in the SMC, but it could be a selection effect, as the SMC sample includes more stars that are brighter and thus more massive. The distribution of the SMC stars along the silicate sequence looks more like the Galactic sample of red supergiants than asymptotic giant branch stars (AGBs). While many of the SMC stars are definitively on the AGB, several also show evidence of hot bottom burning. Three of the supergiants show PAH emission at 11.3 μ m. Two other sources show mixed chemistry, with both carbon-rich and oxygen-rich spectral features. One, MSX SMC 134, may be the first confirmed silicate/carbon star in the SMC. The other, MSX SMC 049, is a candidate post-AGB star. MSX SMC 145, previously considered a candidate OH/IR star, is actually an AGB star with a background galaxy at z = 0.16 along the same line of sight. We consider the overall characteristics of all the MSX sources, the most infrared-bright objects in the SMC, in light of the higher sensitivity and resolution of Spitzer , and compare them with the object types expected from the original selection criteria. This population represents what will be seen in more distant galaxies by the upcoming James Webb Space Telescope ( JWST ). Color–color diagrams generated from the IRS spectra and the mid-infrared filters on JWST show how one can separate evolved stars from young stellar objects (YSOs) and distinguish among different classes of YSOs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Fiber optic Raman thermometer for Space Shuttle main engine preburner profiling

The feasibility of combustion gas temperature measurements in the SSME fuel preburner using nonintrusive optical diagnostics was investigated. Temperature profiles are desired in the high pressure, hydrogen-rich preburner stream to evaluate designs to alleviate thermal stressing of the fuel pump turbine blades. Considering the preburner operating conditions and optical access restrictions, a spontaneous Raman backscattering system, implemented with optical fibers to couple to the combustion device, was selected as the most practical for gas temperature probing. A system is described which employs a remotely-located argon-ion laser to excite the molecular hydrogen Raman spectrum. The laser radiation is conveyed to the combustor through an optical fiber and focused through a window into the chamber by an optical head attached to the combustor. The gas temperature is determined from the distribution of rotational populations represented in the Raman spectrum.

Shirley, J. A.↗
NASA NTRS1993

Dynamically hot galaxies. II - Global stellar populations

The global relationship between the stellar populations and the structural properties of dynamically hot galaxies (DHGs) is investigated using the same sample as was analyzed by Bender et al. (1992), which includes giant ellipticals, low-luminosity ellipticals, compact ellipticals, diffuse dwarf ellipticals, dwarf spheroidals, and bulges. It was found that all DHGs follow a single relationship between global stellar population (represented by Mg2 index or B-V color) and central velocity dispersion sigma(0), and that the Mg2-sigma(0) relation is significantly tighter than the relation between the Mg2 index and absolute luminosity. The relation between central Mg2 index and bulk B-V color was also found to be tight.

Bender, Ralf↗
NASA NTRS1998

An Investigation of Candidate Sensor-Observable Wake Vortex Strength Parameters for the NASA Aircraft Vortex Spacing System (AVOSS)

The counter-rotating pair of wake vortices shed by flying aircraft can pose a threat to ensuing aircraft, particularly on landing approach. To allow adequate time for the vortices to disperse/decay, landing aircraft are required to maintain certain fixed separation distances. The Aircraft Vortex Spacing System (AVOSS), under development at NASA, is designed to prescribe safe aircraft landing approach separation distances appropriate to the ambient weather conditions. A key component of the AVOSS is a ground sensor, to ensure, safety by making wake observations to verify predicted behavior. This task requires knowledge of a flowfield strength metric which gauges the severity of disturbance an encountering aircraft could potentially experience. Several proposed strength metric concepts are defined and evaluated for various combinations of metric parameters and sensor line-of-sight elevation angles. Representative populations of generating and following aircraft types are selected, and their associated wake flowfields are modeled using various wake geometry definitions. Strength metric candidates are then rated and compared based on the correspondence of their computed values to associated aircraft response values, using basic statistical analyses.

Tatnall, Chistopher R.↗
NASA NTRS2001

Far-Infrared Extragalactic Surveys: Past, Present, and Future

As much as one third of the luminosity of the local universe is emitted in the far infrared. In order to understand the history of energy release in the universe, it is crucial to characterize this rest-frame far-infrared contribution from the present back to the era of initial galaxy formation. Over the redshift range from 0 to 10, this energy is received in the 80 micrometers to 1 mm spectral region. In the 1980's the Infrared Astronomy Satellite (IRAS) all-sky survey provided the first comprehensive view of the far infrared emission from the local universe. The diffuse background measurements by Cosmic Background Explorer Satellite (COBE) have provided constraints on the integral contributions from the high redshift universe. In the past five years, submillimeter measurements made using the SCUBA instrument have revealed powerful high redshift sources. To develop a clear history of energy release in the universe, we need numbers and redshifts of representative populations of energetically important objects. The near future will bring the Space Infrared Telescope Facility Multiband Imaging Photometer (SIRTF)(MIPS) survey, which will cover about 100 square degrees at wavelengths out to 160 micrometers, providing a large sample of energetically important galaxies out to z of approx.3. In 2005, the Japanese IRIS survey will provide a 160 micrometers full sky survey, which will provide larger samples of the high z galaxy populations and will find intrinsically rare high luminosity objects. The SPIRE instrument on the FIRST facility will extend these surveys to longer wavelengths, providing a view of the universe at higher redshifts in three spectral bands. A concept for an all-sky submillimeter survey is under development, called the Survey of Infrared Cosmic Evolution (SIRCE). With a 2 m cryogenic telescope, it can map the entire sky to the confusion limit in the 100 to 500 micrometers range in six months. This survey will provide photometric redshifts, number counts, and will find the most luminous objects in the universe. In the next decade, the opening of the submillimeter, combined with the near infrared capability of NGST will provide us with a clear picture of energy release in the early universe.

Moseley, Samuel H., Jr.↗
NASA NTRSDate not supplied

Comparing Two Statistical Models for Low Boom Dose-response Relationships with Correlated Responses

This study compares two statistical modeling approaches to construct summary dose-response curves for low boom community noise surveys. NASA field survey data were used that consist of multiple responses from a survey participant. These data require an approach that accounts for the correlation among repeated annoyance observations from the same participant. A multilevel model accounts for the correlation by allowing estimated parameters to vary with each survey participant. On the other hand, a population average model utilizes generalized estimating equations and accounts for the correlation via a user-specified within-subject correlation structure. A visual comparison of the dose-response curves for these two methods reveals similar results. When comparing specific points along the summary curves, the multilevel model yields more precise confidence bounds than the population average model. The similarity between the summary curves derived from each model lends validity to both approaches for approximating a population representative summary curve.

X-59↗
NASA NTRSDate not supplied

Assessing Risk Due to Small Sample Size in Probability of Detection Analysis Using Tolerance Intervals

Small sample size (e.g.6-30) poses risk in results of probability of detection (POD) analysis using tolerance intervals. This method is also called as the limited sample or LS POD. The analysis is performed either during NDE procedure qualification or for assessment of reliability of an NDE procedure. The risk is primarily due to sampling error. Smaller samples are not likely to be random to the population or representative of the population. The small samples are likely to be biased. Biased samples have smaller standard deviation compared to the population. POD analysis with small biased sample can lead to overestimation of POD. Many sampling schemes are available in statistics to mitigate sampling risk. Primary objective of POD analysis is to determine a decision threshold from signal response measurements of a sample such that it is less than or equal to population decision threshold for 90% POD. Sampling error implies that this NDE reliability condition is violated. One of sampling types is called a representative sample. Representative samples reduce variance in POD estimates but also reduce magnitude of the error. Sampling sensitivity analysis for some sampling types is performed here using repetitive random sampling or Monte Carlo method. Six sampling types are considered for comparison. Some of the sampling types are similar to drawing a representative sample. LS POD model assumes random sampling. Therefore, random sampling is used as a basis for comparison with each sampling type. The sampling types used in the analysis are, A. Nominal and worst-case sampling, B. Worst-case sampling, C. Nominal case sampling, D. Random sampling, E. Random target, and sub-target sampling. F. Nominal target and sub-target sampling. Results of Monte Carlo simulation indicate that type F sampling can mitigate sampling risk and is also more practical to implement. Type A sampling may also mitigate the sampling risk, but it may be less practical to implement.

Ajay M Koshti↗
DOE OSTI2019

The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use

Population data represent an essential component in studies focusing on human–nature interrelationships, disaster risk assessment and environmental health. Several recent efforts have produced global- and continental-extent gridded population data which are becoming increasingly popular among various research communities. However, these data products, which are of very different characteristics and based on different modeling assumptions, have never been systematically reviewed and compared, which may impede their appropriate use. This article fills this gap and presents, compares and discusses a set of large-scale (global and continental) gridded datasets representing population counts or densities. It focuses on data properties, methodological approaches and relative quality aspects that are important to fully understand the characteristics of the data with regard to the intended uses. Written by the data producers and members of the user community, through the lens of the “fitness for use” concept, the aim of this paper is to provide potential data users with the knowledge base needed to make informed decisions about the appropriateness of the data products available in relation to the target application and for critical analysis.

58 GEOSCIENCES↗
DOE OSTI2024

Multi-Attribute Subset Selection enables prediction of representative phenotypes across microbial populations

The interpretation of complex biological datasets requires the identification of representative variables that describe the data without critical information loss. This is particularly important in the analysis of large phenotypic datasets (phenomics). Here we introduce Multi-Attribute Subset Selection (MASS), an algorithm which separates a matrix of phenotypes (e.g., yield across microbial species and environmental conditions) into predictor and response sets of conditions. Using mixed integer linear programming, MASS expresses the response conditions as a linear combination of the predictor conditions, while simultaneously searching for the optimally descriptive set of predictors. We apply the algorithm to three microbial datasets and identify environmental conditions that predict phenotypes under other conditions, providing biologically interpretable axes for strain discrimination. MASS could be used to reduce the number of experiments needed to identify species or to map their metabolic capabilities. The generality of the algorithm allows addressing subset selection problems in areas beyond biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

LandScan Global 30 Arcsecond Annual Global Gridded Population Datasets from 2000 to 2022

Abstract Oak Ridge National Laboratory (ORNL) annually develops the LandScan Global (LSG) dataset, a 30 arcsecond global gridded population dataset representing global ambient human population distribution. This multivariable dasymetric model disaggregates census counts within administrative boundaries using ancillary data. Each country’s distribution reflects cultural and socioeconomic patterns; manual validations yield a unique global dataset for assessing populations at risk. For over two decades, LSG has been a standard for estimating populations at risk, aiding U.S. federal government, academia and humanitarian organizations. During disasters such as the 2004 Indian Ocean tsunami and the 2010 Haiti earthquake and geopolitical crises such as the Syrian civil war and the 2022 Russian invasion of Ukraine, LSG supported scientific and operational communities in emergency response and recovery. In 2022, LSG datasets from 2000 onward were made publicly available through ORNL’s LandScan Portal. This data descriptor details our methodology and the application of geospatial science and machine learning to geographic and demographic data, highlighting uses in urban resiliency, emergency management, disaster response, and human health and security.

Science & Technology - Other Topics↗
DOE OSTI2023

The Chemodynamics of the Stellar Populations in M31 from APOGEE Integrated-light Spectroscopy

We present an analysis of nearly 1000 near-infrared, integrated-light spectra from APOGEE in the inner ~7 kpc of M31. We utilize full-spectrum fitting with A-LIST simple stellar population spectral templates that represent a population of stars with the same age, [M/H], and [α/M]. With this, we determine the mean kinematics, metallicities, α abundances, and ages of the stellar populations of M31's bar, bulge, and inner disk (~4–7 kpc). We find a nonaxisymmetric velocity field in M31 resulting from the presence of a bar. The bulge of M31 is less metal-rich (mean [M/H] = $0.149$$^{+0.067}_{-0.081}$ dex) than the disk, features minima in metallicity on either side of the bar ([M/H] ~ -0.2), and is enhanced in α abundance (mean [α/M] = $0.281$$^{+0.035}_{-0.038}$). The disk of M31 within ~7 kpc is enhanced in both metallicity ([M/H] = $-0.023$$^{+0.050}_{-0.052}$) and α abundance ([α/M] = $0.274$$^{+0.020}_{-0.025}$). Both of these structural components are uniformly old at ≃12 Gyr. We find the mean metallicity increases with distance from the center of M31, with the steepest gradient along the disk major axis (0.043 ± 0.021 dex kpc -1 ). This gradient is the result of changing light contributions from the bulge and disk. The chemodynamics of stellar populations encodes information about a galaxy's chemical enrichment, star formation history, and merger history, allowing us to discuss new constraints on M31's formation. Our results provide a stepping stone between our understanding of the Milky Way and other external galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

LandScan Global 2023: Silver Edition

For a quarter of a century, the LandScan Global (LSG) project has annually released a global, high-resolution gridded population dataset representing the ambient or unwarned population at a 30 arcsecond resolution. LSG supports a range of applications such as emergency management, disaster response, and human health and security for understanding populations at risk. The 2023 release of LSG, the LandScan Silver Edition, represents a major methodological leap forward while also leveraging previous knowledge—the previous year was the baseline for the current annual update carrying forward valuable knowledge of the built environment for the past quarter century—to train the machine learning models. Compared with annual releases over the past 24years, multiple advancements were made to different aspects of the methodology to achieve reproducibility, transparency, and consistent global propagation of solutions to modeling or population distribution issues identified during the review process. These novel changes include incorporation of the latest available geospatial inputs across the globe, machine learning models instead of manual modifications, population feature importance analysis, open-source solutions vs. proprietary software, generation of multiple global versions, analytic validations, and human-in-the-loop revisions to produce the final version. Additionally, algorithms—such as anomaly detection—were introduced to quickly identify areas of focus to develop a new and robust systematic review. Significant changes in modeled population distributions were observed between the 2022 and 2023 releases, largely attributable to improvements in data and methods and discussed thoroughly within this report. In summation, the LandScan Silver Edition leverages the best of the past quarter century of LSG legacy knowledge and continues a tradition of applying cutting-edge enhancements to serve as a new benchmark for accurate, actionable gridded population data

Lebakula, Viswadeep↗
NASA NTRS1980

Phobos and deimos: Analysis of surface features, ejecta dynamics and a volatile loss mechanism

The question of whether the crater population on Phobos represents a production population or an equilibrium population is considered. The absolute ages of cratered surfaces are interpreted and analyzed. A computer program was developed to study the dynamics of material ejected from Martian satellites and to investigate the hypothesis that at least some of the extensive set of linear features discovered on the surface of Phobos could be the result of secondary cratering from the Stickney impact. The possibility that Deimos was catastrophically disrupted by a large impact but subsequently reaccreted is considered as well as the probability the Phobos had an impact nearly large enough to disrupt it are also discussed.

Davis, D. R.↗
DOE OSTI2020

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth’s atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently-developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

First Report and Molecular Variability of Belonolaimus longicaudatus Associated with Turfgrass in Maryland

Abstract Turfgrass is a crop used extensively in athletic fields and golf courses in Maryland. A soil sample collected in July 2023 from an athletic field in Baltimore County, Maryland, part of a turfgrass nematode survey, containedBelonolaimus longicaudatus. In the southeastern United States,B. longicaudatusis an economically important pathogen of warm season turfgrass. The density was four individuals/100 cm 3 of soil, and no visual symptoms were observed in the bermudagrass field. Morphological features and morphometrics of males and females were consistent withB. longicaudatusand placed the Maryland population in a subclade that was geographically represented by populations from north and west Florida, Texas, and South Carolina. Sequencing of the internal transcribed spacer region ITS1 and ITS2 and 28S large ribosomal subunit D2-23 expansion region confirmed the species' identity. Phylogenetic trees and parsimony network analysis placed the Maryland isolate in a large grouping ofB. longicaudatuspopulations including those from Alabama, Delaware, Florida, Indiana, Mississippi, South Carolina, and Texas. To our knowledge, this is the first report ofB. longicaudatusin Maryland.

Zoology↗