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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Carbon-Binder Optimization for Lithium-Ion Battery Extreme Fast Charge

Battery performance is strongly correlated with electrode microstructure and weight loading of the electrode components. Among them are the carbon-black and binder additives that enhance effective conductivity and provide mechanical integrity. However, these both reduce effective ionic transport in the electrolyte phase and reduce energy density. Therefore, an optimal additive loading is required to maximize performance, especially for fast charging where ionic transport is essential. Such optimization analysis is however challenging due to the nanoscale imaging limitations that prevent characterizing this additive phase and thus quantifying its impact on performance. Herein, an additive-phase generation algorithm has been developed to remedy this limitation and identify percolation threshold used to define a minimal additive loading. Improved ionic transport coefficients from reducing additive loading has been then quantified through homogenization calculation, macroscale model fitting, and experimental symmetric cell measurement, with good agreement between the methods. Rate capability test demonstrates capacity improvement at fast charge at the beginning of life, from 37% to 55%, respectively for high and low additive loading during 6C CC charging, in agreement with macroscale model, and attributed to a combination of lower cathode impedance, reduced electrode tortuosity and cathode thickness.

carbon-binder additives↗
DOE OSTI2015

Status Report - Softwood Fiberboard Properties And Degradation Rates For Storage Of The 9975 Shipping Package In KAC

Thermal, mechanical and physical properties have been measured on softwood fiberboard samples following accelerated aging for up to approximately 7 years. The aging environments have included elevated temperature < 250 ºF (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. The results from this testing have been analyzed, and preliminary aging models fit to the data. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions and density) to their rate of change in potential storage environments have been developed. Combined with acceptance criteria and an estimate of the actual conditions the fiberboard experiences in KAC, these models allow development of service life predictions.

42 ENGINEERING↗
DOE OSTI2016

The connection between the host halo and the satellite galaxies of the Milky Way

Many properties of the Milky Way's (MW) dark matter halo, including its mass-assembly history, concentration, and subhalo population, remain poorly constrained. We explore the connection between these properties of the MW and its satellite galaxy population, especially the implication of the presence of the Magellanic Clouds for the properties of the MW halo. Using a suite of high-resolution N-body simulations of MW-mass halos with a fixed final ${M}_{\mathrm{vir}}\sim {10}^{12.1}\,{M}_{\odot }$, we find that the presence of Magellanic Cloud-like satellites strongly correlates with the assembly history, concentration, and subhalo population of the host halo, such that MW-mass systems with Magellanic Clouds have lower concentration, more rapid recent accretion, and more massive subhalos than typical halos of the same mass. Using a flexible semi-analytic galaxy formation model that is tuned to reproduce the stellar mass function of the classical dwarf galaxies of the MW with Markov-Chain Monte-Carlo, we show that adopting host halos with different mass-assembly histories and concentrations can lead to different best-fit models for galaxy-formation physics, especially for the strength of feedback. These biases arise because the presence of the Magellanic Clouds boosts the overall population of high-mass subhalos, thus requiring a different stellar-mass-to-halo-mass ratio to match the data. These biases also lead to significant differences in the mass–metallicity relation, the kinematics of low-mass satellites, the number counts of small satellites associated with the Magellanic Clouds, and the stellar mass of MW itself. Finally, observations of these galaxy properties can thus provide useful constraints on the properties of the MW halo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Predicting fatigue from heart rate signatures using functional logistic regression

Physical fatigue can have adverse effects on humans in extreme environments. Therefore, being able to predict fatigue using easy to measure metrics such as heart rate (HR) signatures has potential to have an impact in real-life scenarios. We apply a functional logistic regression model that uses HR signatures to predict physical fatigue, where physical fatigue is defined in a data-driven manner. Data were collected using commercially available wearable devices on 47 participants hiking the 20.7-mile Grand Canyon rim-to-rim trail in a single day. Fitted model provides good predictions and interpretable parameters for real-life application.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

The XMM Cluster Survey: the halo occupation number of BOSS galaxies in X-ray clusters

We present a direct measurement of the mean halo occupation distribution (HOD) of galaxies taken from the eleventh data release (DR11) of the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS). The HOD of BOSS low-redshift (LOWZ: 0.2 < z < 0.4) and Constant-Mass (CMASS: 0.43 < z <0.7) galaxies is inferred via their association with the dark matter haloes of 174 X-ray-selected galaxy clusters drawn from the XMM Cluster Survey (XCS). Halo masses are determined for each galaxy cluster based on X-ray temperature measurements, and range between log 10 (M 180 /M ⊙ ) = 13 and 15. Our directly measured HODs are consistent with the HOD-model fits inferred via the galaxy-clustering analyses of Parejko et al. for the BOSS LOWZ sample and White et al. for the BOSS CMASS sample. Under the simplifying assumption that the other parameters that describe the HOD hold the values measured by these authors, we have determined a best-fitting alpha-index of 0.91 ± 0.08 and 1.27$^{+0.03}_{-0.04} $ for the CMASS and LOWZ HOD, respectively. These alpha-index values are consistent with those measured by White et al. and Parejko et al. In summary, our study provides independent support for the HOD models assumed during the development of the BOSS mock-galaxy catalogues that have subsequently been used to derive BOSS cosmological constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

Jacobs, John M.↗
DOE OSTI2020

Heavy flavor dynamics across system size at the LHC

One of the fundamental signatures of the Quark Gluon Plasma has been the suppression of heavy flavor (specifically D mesons), which has been measured via the nuclear modification factor, R AA and azimuthal anisotropies, v n , in large systems. However, multiple competing models can reproduce the same data for R AA to v n . In this talk we break down the competing effects that conspire together to successfully reproduce R AA and v n in experimental data using Trento+v-USPhydro+DAB-MOD. Then using our best fit model we make predictions for R AA and v n across system size for 208 PbPb, 129 XeXe, 40 ArAr, and 16 OO collisions. We find that 0–10% centrality has a non-trivial interplay between the system size and eccentricities such that system size effects are masked in v 2 whereas in 30–50% centrality the eccentricities are approximately constant across system size and, therefore, is a better centrality class to study D meson dynamics across system size.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species

Understanding the microbial genomic contributors to antimicrobial resistance (AMR) is essential for early detection of emerging AMR infections, a pressing global health threat in human and veterinary medicine. Here we used whole genome sequencing and antibiotic susceptibility test data from 980 disease causing Escherichia coli isolated from companion and farm animals to model AMR genotypes and phenotypes for 24 antibiotics. We determined the strength of genotype-to-phenotype relationships for 197 AMR genes with elastic net logistic regression. Model predictors were designed to evaluate different potential modes of AMR genotype translation into resistance phenotypes. Our results show a model that considers the presence of individual AMR genes and total number of AMR genes present from a set of genes known to confer resistance was able to accurately predict isolate resistance on average (mean F 1 score = 98.0%, SD = 2.3%, mean accuracy = 98.2%, SD = 2.7%). However, fitted models sometimes varied for antibiotics in the same class and for the same antibiotic across animal hosts, suggesting heterogeneity in the genetic determinants of AMR resistance. We conclude that an interpretable AMR prediction model can be used to accurately predict resistance phenotypes across multiple host species and reveal testable hypotheses about how the mechanism of resistance may vary across antibiotics within the same class and across animal hosts for the same antibiotic.

Chung, Henri C.↗
DOE OSTI2017

Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this work, a differential evolution adaptive Metropolis (DREAM) algorithm is used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The calibration of DREAM results in a better model fit and predictive performance compared to the popular adaptive Metropolis (AM) scheme. Moreover, DREAM indicates that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identifies one mode. The application suggests that DREAM is very suitable to calibrate complex terrestrial ecosystem models, where the uncertain parameter size is usually large and existence of local optima is always a concern. In addition, this effort justifies the assumptions of the error model used in Bayesian calibration according to the residual analysis. Here, the result indicates that a heteroscedastic, correlated, Gaussian error model is appropriate for the problem, and the consequent constructed likelihood function can alleviate the underestimation of parameter uncertainty that is usually caused by using uncorrelated error models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Correcting nonlinearity and mass-bias in measurements by ICP quadrupole mass spectrometry

A two-parameter modeling formula is proposed for quadrupole ICP-MS (ICP-QMS) data, which corrects for nonlinearity with a “dead-time” function and makes subsequent weighted mass-bias corrections to normalize isotope ratio data to pertinent isotopic reference materials. The methodology improves the short-term and long-term precision as well as accuracy of the measurements. Applying the model to isotopes spanning a wide mass range revealed that values for the parameters describing nonlinearity and mass bias do not conform to expectations based on conventional interpretation. Within a single analysis run for a specific element, nonlinearity and mass-bias corrections can be evaluated to very tight tolerances and the model fits the data to within a few parts per thousand. However, in a different run or with a different element, the values of the parameters might change. A comprehensive strategy for conducting measurements of isotope ratios or trace-element concentrations is described, which takes advantage of the model’s strengths and accommodates the observed run-to-run variations. in conclusion, supporting data is presented to demonstrate improved precision and accuracy with the widely available ICP-QMS system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Microbial dormancy improves development and experimental validation of ecosystem model

Climate feedbacks from soils can result from environmental change followed by response of plant and microbial communities, and/or associated changes in nutrient cycling. Explicit consideration of microbial life history traits and functions may be necessary to predict climate feedbacks due to changes in the physiology and community composition of microbes and their associated effect on carbon cycling. Here, we enhanced the Microbial-Enzyme-mediated Decomposition (MEND) model by incorporating microbial dormancy and the ability to track multiple isotopes of carbon. We tested two versions of MEND, i.e., MEND with dormancy and MEND without dormancy, against long-term (270 d) lab incubations of four soils with isotopically-labeled substrates. MEND without dormancy adequately fitted multiple observations (total and 14C respiration, and dissolved organic carbon), but at the cost of significantly underestimating the total microbial biomass. The MEND with dormancy improved estimates of microbial biomass by 20 71% over the MEND without dormancy. We observed large differences for two fitted model parameters, the specific maintenance and growth rates for active microbes, depending on whether dormancy was considered. Together our model extrapolations of the incubation study show that long-term soil incubations with observations in multiple carbon pools are necessary to estimate both decomposition and microbial parameters. These efforts should provide essential support to future field- and global-scale simulations and enable more confident predictions of feedbacks between environmental change and carbon cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

THE HST/ACS+WFC3 SURVEY FOR LYMAN LIMIT SYSTEMS. II. SCIENCE

We present the first science results from our Hubble Space Telescope survey for Lyman limit absorption systems (LLS) using the low dispersion spectroscopic modes of the Advanced Camera for Surveys and the Wide Field Camera 3. Through an analysis of 71 quasars, we determine the incidence frequency of LLS per unit redshift and per unit path length, l(z) and l(X), respectively, over the redshift range 1 < z < 2.6, and find a weighted mean of l(X) =0.29 {+-} 0.05 for 2.0 < z < 2.5 through a joint analysis of our sample and that of Ribaudo et al. Through stacked spectrum analysis, we determine a median (mean) value of the mean free path to ionizing radiation at z = 2.4 of {lambda}{sup 912}{sub mfp} = 243(252) h {sup -1}{sub 72} Mpc, with an error on the mean value of {+-}43 h {sup -1}{sub 72} Mpc. We also re-evaluate the estimates of {lambda}{sup 912}{sub mfp} from Prochaska et al. and place constraints on the evolution of {lambda}{sup 912}{sub mfp} with redshift, including an estimate of the ''breakthrough'' redshift of z = 1.6. Consistent with results at higher z, we find that a significant fraction of the opacity for absorption of ionizing photons comes from systems with N{sub H{sub I}} {<=}10{sup 17.5} cm{sup -2} with a value for the total Lyman opacity of {tau}{sup Lyman}{sub eff} = 0.40 {+-} 0.15. Finally, we determine that at minimum, a 5-parameter (4 power law) model is needed to describe the column density distribution function f(N{sub H{sub I}}, X) at z {approx} 2.4, find that f(N{sub H{sub I}}, X) undergoes no significant change in shape between z {approx} 2.4 and z {approx} 3.7, and provide our best fit model for f(N{sub H{sub I}}, X).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

MID-INFRARED HIGH-CONTRAST IMAGING OF HD 114174 B: AN APPARENT AGE DISCREPANCY IN A ''SIRIUS-LIKE'' BINARY SYSTEM

We present new observations of the faint ''Sirius-like'' companion discovered to orbit HD 114174. Previous attempts to image HD 114174 B at mid-infrared wavelengths using NIRC2 at Keck have resulted in a non-detection. Our new L'-band observations taken with the Large Binocular Telescope and L/M-band InfraRed Camera recover the companion (ΔL = 10.15 ± 0.15 mag, ρ = 0.''675 ± 0.''016) with a high signal-to-noise ratio (10σ). This measurement represents the deepest L' high-contrast imaging detection at subarcsecond separations to date, including extrasolar planets. We confirm that HD 114174 B has near-infrared colors consistent with the interpretation of a cool white dwarf (WD; J – L' = 0.76 ± 0.19 mag, K – L' = 0.64 ± 0.20). New model fits to the object's spectral energy distribution indicate a temperature T {sub eff} = 4260 ± 360 K, surface gravity log g = 7.94 ± 0.03, a cooling age t{sub c} ≈ 7.8 Gyr, and mass M = 0.54 ± 0.01 M {sub ☉}. We find that the cooling ages given by theoretical atmospheric models do not agree with the age of HD 114174 A derived from both isochronological and gyrochronological analyses. We speculate on possible scenarios to explain the apparent age discrepancy between the primary and secondary. HD 114174 B is a nearby benchmark WD that will ultimately enable a dynamical mass estimate through continued Doppler and astrometric monitoring. Efforts to characterize its physical properties in detail will test theoretical atmospheric models and improve our understanding of WD evolution, cooling, and progenitor masses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Measurement of the effective leptonic weak mixing angle

Using pp collision data at $\sqrt{s}$ = 13 TeV, recorded by the LHCb experiment between 2016 and 2018 and corresponding to an integrated luminosity of 5.4 fb −1 , the forward-backward asymmetry in the pp → Z/γ* → μ + μ − process is measured. The measurement is carried out in ten intervals of the difference between the muon pseudorapidities, within a fiducial region covering dimuon masses between 66 and 116 GeV, muon pseudorapidities between 2.0 and 4.5 and muon transverse momenta above 20 GeV. These forward-backward asymmetries are compared with predictions, at next-to-leading order in the strong and electroweak couplings. The measured effective leptonic weak mixing angle is ${\sin}^2{\theta}_{\textrm{eff}}^{\ell }=0.23147\pm 0.00044\pm 0.00005\pm 0.00023,$ where the first uncertainty is statistical, the second arises from systematic uncertainties associated with the asymmetry measurement, and the third arises from uncertainties in the fit model used to extract ${\sin}^2{\theta}_{\textrm{eff}}^{\ell }$ from the asymmetry measurement. This result is based on an arithmetic average of results using the CT18, MSHT20, and NNPDF31 parameterisations of the proton internal structure, and is consistent with previous measurements and with predictions from the global electroweak fit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Enhanced mechanical property evaluation using innovative data analytics capability

This report focuses on efforts to improve Multiphysics Object-Oriented Simulation Environ-ment (MOOSE) for mechanical property evaluation using data analytics. These efforts involveimprovements to the stochastic tools module (STM) for stochastic simulations of MOOSE mul-tiphysics model and the development of inverse optimization capabilities. The report gives anoverview of the STM and describes recent updates to its core capabilities and theory on itsreduced-order model (ROM) schemes. Examples are also provided showing the impact of theseupdates and exhibits the usefulness of ROMs. An overview of the gradient based inverse opti-mziation algorithms are given along with examples of their application to source identification.Inverse optimization will provide a new methodology in STM for fitting model parameters toexperimental data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice

Positron emission tomography (PET) radioligands that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[ 18 F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [ 18 F]Nifene, displaying similar pKa and binding affinity to nicotine. Time–activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the β2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

2-FA85380↗
DOE OSTI2017

Predicted Extension of the Sagittarius Stream to the Milky Way Virial Radius

The extensive span of the Sagittarius (Sgr) stream makes it a promising tool for studying the gravitational potential of the Milky Way (MW). Characterizing its stellar kinematics can constrain halo properties and provide a benchmark for the paradigm of galaxy formation from cold dark matter. Accurate models of the disruption dynamics of the Sgr progenitor are necessary to employ this tool. Using a combination of analytic modeling and N -body simulations, we build a new model of the Sgr orbit and resulting stellar stream. In contrast to previous models, we simulate the full infall trajectory of the Sgr progenitor from the time it first crossed the MW virial radius 8 Gyr ago. An exploration of the parameter space of initial phase-space conditions yields tight constraints on the angular momentum of the Sgr progenitor. Our best-fit model is the first to accurately reproduce existing data on the 3D positions and radial velocities of the debris detected 100 kpc away in the MW halo. In addition to replicating the mapped stream, the simulation also predicts the existence of several arms of the Sgr stream extending to hundreds of kiloparsecs. The two most distant stars known in the MW halo coincide with the predicted structure. Additional stars in the newly predicted arms can be found with future data from the Large Synoptic Survey Telescope. Detecting a statistical sample of stars in the most distant Sgr arms would provide an opportunity to constrain the MW potential out to unprecedented Galactocentric radii.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016

Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90% of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. We observed systematic biases ranging from -31% (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130-Mg ha -1 (pantropical), when predicting AGB (dry mass) over scenarios using our different models and an available pantropical model. Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. Furthermore, the model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.

54 ENVIRONMENTAL SCIENCES↗