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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluation of data collection bias of third molar stages of mineralisation for age estimation in the living

Abstract Age assessment of the living is a fundamental procedure in the process of human identification, in order to guarantee fair treatment of individuals, which has ethical, civil, legal, and medical repercussions. The careful selection of the appropriate methods requires evaluation of several parameters: accuracy, precision of the method, as well as its reproducibility. The approach proposed by Mincer et al. adapted from Demirjian et al. exploring third molar mineralisation, is one of the most frequently considered for age estimation of the living. Thus, this work aims to assess potential bias in the data collection when applying the classification stages for dental mineralisation adapted by Mincer et al. A total of 102 orthopantomographs, of clinical origin, belonging to individuals aged between 12 and 25 years ($ \bar{\textit x} $ = 20.12 years, SD = 3.49 years; 65 females, 37 males, all of Portuguese nationality) were included and a retrospective analysis performed by five observers with different levels of experience (high, average, and basic). The performance and agreement between five observers were evaluated using Weighted Cohen’s Kappa and the Intraclass Correlation Coefficient. To access the influence of impaction on third molar classification, variables were tested using ordinal logistic regression Generalised Linear Model. It was observed that there were variations in the number of teeth identified among the observers, but the agreement levels ranged from moderate to substantial (0.4–0.8). Upon closer examination of the results, it was observed that although there were discernible differences between highly experienced observers and those with less experience, the gap was not as significant as initially hypothesised, and a greater disparity between the classifications of the upper (0.24–0.49) and lower third molars (>0.55) was observed. When bone superimposition is present, the classification process is not significantly influenced; however, variation in teeth angulation affects the assessment. The results suggest that with an efficient preparation, the level of experience as a factor can be overcome. Mincer and colleague's classification system can be replicated with ease and consistency, even though the classification of upper and lower third molars presents distinct challenges.

de Oliveira Santos, Inês (ORCID:0000000267324347)↗
DOE OSTI2020

High resolution X-ray spectroscopy of Supergiant HMXB 4U1700-37 during the compact object eclipse.

In this work, we present an analysis of the first observation of the iconic High Mass X-ray Binary 4U 1700-37 with the Chandra High Energy Transmission Gratings during an X-ray eclipse. The goal of the observation was to study the structure/physical conditions in the clumpy stellar wind through high resolution spectroscopy. We find that: a) emission line brightness from K shell transitions, corresponding to near neutral species, directly correlates with continuum illumination. However, these lines do not greatly diminish during eclipse. This is readily explained if fluorescence Kα emission comes from the bulk of the wind. b) The highly ionised Fe xxv and Fe xxvi Lyα diminish during eclipse. Thus, they must be produced in the vicinity of the compact object where log ξ > 3. c) to describe the emission line spectrum, the sum of two self consistent photo ionisation models with low ionisation (log ξ ~ -1) and high ionisation (log ξ ~2.4) is required. From their emission measures, the clump-to-interclump density ratio can be estimated to be nc/ni ~ 300. To fit the complex He-like Si xiii profile, the plasma requires a broadening with vbulk ~ 840 km s-1. Reproducing the observed r ≈ f line fluxes requires the addition of a third collisionally ionised plasma. d) Emission lines widths appear unresolved at the hetg gratings resolution with exception of Silicon. There is no clear radial segregation between (quasi)neutral and ionised species, consistent with cold wind clumps interspersed in a hot rarefied interclump medium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Galaxy morphological classification catalogue of the Dark Energy Survey Year 3 data with convolutional neural networks

ABSTRACT We present in this paper one of the largest galaxy morphological classification catalogues to date, including over 20 million galaxies, using the Dark Energy Survey (DES) Year 3 data based on convolutional neural networks (CNNs). Monochromatic i-band DES images with linear, logarithmic, and gradient scales, matched with debiased visual classifications from the Galaxy Zoo 1 (GZ1) catalogue, are used to train our CNN models. With a training set including bright galaxies (16 ≤ i < 18) at low redshift (z < 0.25), we furthermore investigate the limit of the accuracy of our predictions applied to galaxies at fainter magnitude and at higher redshifts. Our final catalogue covers magnitudes 16 ≤ i < 21, and redshifts z < 1.0, and provides predicted probabilities to two galaxy types – ellipticals and spirals (disc galaxies). Our CNN classifications reveal an accuracy of over 99 per cent for bright galaxies when comparing with the GZ1 classifications (i < 18). For fainter galaxies, the visual classification carried out by three of the co-authors shows that the CNN classifier correctly categorizes discy galaxies with rounder and blurred features, which humans often incorrectly visually classify as ellipticals. As a part of the validation, we carry out one of the largest examinations of non-parametric methods, including ∼100 ,000 galaxies with the same coverage of magnitude and redshift as the training set from our catalogue. We find that the Gini coefficient is the best single parameter discriminator between ellipticals and spirals for this data set.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A step towards unveiling the nature of three cataclysmic variables: LS Cam, V902 Mon, and SWIFT J0746.3-1608

ABSTRACT We have carried out detailed time-resolved timing analyses of three cataclysmic variables (CVs) namely LS Cam, V902 Mon, and SWIFT J0746.3-1608, using the long-baseline, high-cadence optical photometric data from the Transiting Exoplanet Survey Satellite. Our analysis of LS Cam observations hints the presence of a superorbital period of ∼4.025 ± 0.007 d along with negative and positive superhump periods of ∼3.30 and 3.70 h, respectively. These results can be explained as an interaction of nodal and apsidal precession of the accretion disc with orbital motion. For the other two sources, V902 Mon and SWIFT J0746.3-1608, we have found evidence of a beat period of 2387.0 ± 0.6 and 2409.5 ± 0.7 s, respectively, which were not found in earlier studies. Our results presented in this study indicate the change in the accretion mode during the entire observing period for both sources. For V902 Mon, an apparent orbital period derivative of (6.09 ± 0.60) × 10−10 was also found. Moreover, the second harmonic of orbital frequency dominates the power spectrum of SWIFT J0746.3-1608, suggestive of ellipsoidal modulation of the secondary star. Present analyses suggest that LS Cam could be a superhumping CV, whereas V902 Mon and SWIFT J0746.3-1608 are likely to be variable disc-overflow accreting intermediate polars.

Rawat, Nikita (ORCID:0000000246336832)↗
DOE OSTI2026

Effect of recoils on soft-drop-groomed observables in 𝛾-tagged jets in a multistage approach

We investigate medium-induced modifications to jet substructure observables that characterize hard components in central Pb-Pb collisions at $\sqrt{𝑠_{𝑁⁢𝑁}}$ = 5.02 TeV. Using a multistage Monte Carlo simulation of in-medium jet shower evolution, we explore flavor-dependent medium effects through simulations of inclusive and 𝛾-tagged jets. The results show that quark jets undergo a nonmonotonic modification compared with gluon jets in observables such as the Pb-Pb to 𝑝−𝑝 ratio of the soft drop prong angle 𝑟 𝑔 , the relative prong transverse momentum 𝑘 𝑇,𝑔 , and the groomed mass 𝑚 𝑔 distributions. Due to this nonmonotonic modification, 𝛾-tagged jets, enriched in quark jets, provide surprisingly clear signals of medium-induced structural modifications, distinct from effects dominated by selection bias. Further systematic studies demonstrate that these effects are dominated by recoil medium response. This work highlights the potential of hard substructures in 𝛾-tagged jets as powerful tools for probing the jet-medium interactions in high-energy heavy-ion collisions, in particular by enabling detailed investigations of jet-medium parton scatterings via their associated medium response. All simulations for 𝛾-tagged jet analyses carried out in this paper used triggered events containing at least one hard photon, which highlights the utility of these observables for future Bayesian analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Transverse energy-energy correlators in the color-glass condensate at the electron-ion collider

We investigate the transverse energy-energy correlators (TEEC) in the small- x regime at the upcoming Electron-Ion Collider (EIC). Focusing on the back-to-back production of electron-hadron pairs in both e p and e A collisions, we establish a factorization formula given in terms of the hard function, quark distributions, soft functions, and TEEC jet functions, where the gluon saturation effect is incorporated. Numerical results for TEEC in both e p and e A collisions are presented, together with the nuclear modification factor R A . Our analysis reveals that TEEC observables in deep inelastic scattering provide a valuable approach for probing gluon saturation phenomena. Our findings underscore the significance of measuring TEEC at the EIC, emphasizing its efficacy in advancing our understanding of gluon saturation and nuclear modifications in high-energy collisions. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2022

DERMS Online: A New Voltage Sensitivity-Enabled Feedback Optimization Framework

This paper proposes a distributed energy resource management system (DERMS) solution by developing a new voltage sensitivity-enabled feedback optimization framework. The key idea is to adopt a measurement feedback scheme to reformulate the original nonlinear optimization into a linear programming (LP) problem via perturb-and-observe-based voltage sensitivity analysis. The proposed solution eliminates the dependence on load knowledge and can be implemented online thanks to an efficient open-source solver for LP problems. Comparison results with other control methods on a real distribution feeder in Southern California highlight the feasibility as well as benefits for the proposed framework.

distributed energy resource management↗
DOE OSTI2026

Alkali Vapor Corrosion of Spinel (MgAl 2 O 4 ) and Gahnite (ZnAl 2 O 4 ) Refractories—A Comparative Study

Alkali vapor corrosion is critical for refractories used in the kilns and furnaces of diverse high-temperature processing and manufacturing sectors such as gasifiers, cement production, and glass making. Gahnite (ZnAl 2 O 4 ) is being investigated as a potential chrome-free refractory because of its similarity with the structure and properties of magnesium aluminate (MgAl 2 O 4 ) spinel. The alkali vapor corrosion of ZnAl 2 O 4 , MgAl 2 O 4 , and Mg 0.5 Zn 0.5 Al 2 O 4 was studied, according to ASTM C987-10, at 1371°C for 24 h using sodium carbonate (Na 2 CO 3 ). The surface and the polished cross-sections of the corroded ZnAl 2 O 4 , MgAl 2 O 4 , and Mg 0.5 Zn 0.5 Al 2 O 4 specimens were analyzed using x-ray diffraction (XRD), microscopy, and energy-dispersive spectroscopy (EDS) techniques. MgO in MgAl 2 O 4 , ZnO in ZnAl 2 O 4 , Mg 0.77 Zn 0.23 O, and NaAlO 2 were detected as the corrosion products for these specimens. The extent of corrosion substantially varied among the specimens despite the similarity in the corrosion products. The corrosion resistance increased in the following order: Mg 0.5 Zn 0.5 Al 2 O 4 > MgAl 2 O 4 > ZnAl 2 O 4 . The formation of a dense MgO and Mg 0.77 Zn 0.23 O layer for MgAl 2 O 4 and Mg 0.5 Zn 0.5 Al 2 O 4 , respectively, contributed to their superior resistance to alkali vapor corrosion. The underlying corrosion mechanisms are discussed based on experimental observations supported by thermodynamic analysis. Additionally, the results suggest that a partial Zn 2+ substitution for Mg 2+ in MgAl 2 O 4 can enhance the resistance to alkali vapor corrosion.

alkali corrosion↗
DOE OSTI2021

Fine-root functional trait responses to experimental warming: a global meta-analysis

Whether and how warming alters functional traits of absorptive plant roots remains to be answered across the globe. Tackling this question is crucial to better understanding terrestrial responses to climate change as fine-root traits drive many ecosystem processes. In this work, we carried out a detailed synthesis of fine-root trait responses to experimental warming by performing a meta-analysis of 964 paired observations from 177 publications. Warming increased fine-root biomass, production, respiration and nitrogen concentration as well as decreased root carbon : nitrogen ratio and nonstructural carbohydrates. Warming effects on fine-root biomass decreased with greater warming magnitude, especially in short-term experiments. Furthermore, the positive effect of warming on fine-root biomass was strongest in deeper soil horizons and in colder and drier regions. Total fine-root length, morphology, mortality, life span and turnover were unresponsive to warming. Our results highlight the significant changes in fine-root traits in response to warming as well as the importance of warming magnitude and duration in understanding fine-root responses. These changes have strong implications for global soil carbon stocks in a warmer world associated with increased root-derived carbon inputs into deeper soil horizons and increases in fine-root respiration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Interpreting and Stabilizing Machine-Learning Parametrizations of Convection

Neural networks are a promising technique for parameterizing subgrid-scale physics (e.g., moist atmospheric convection) in coarse-resolution climate models, but their lack of interpretability and reliability prevents widespread adoption. For instance, it is not fully understood why neural network parameterizations often cause dramatic instability when coupled to atmospheric fluid dynamics. This paper introduces tools for interpreting their behavior that are customized to the parameterization task. First, we assess the nonlinear sensitivity of a neural network to lower-tropospheric stability and the midtropospheric moisture, two widely studied controls of moist convection. Second, we couple the linearized response functions of these neural networks to simplified gravity wave dynamics, and analytically diagnose the corresponding phase speeds, growth rates, wavelengths, and spatial structures. To demonstrate their versatility, these techniques are tested on two sets of neural networks, one trained with a super-parameterized version of the Community Atmosphere Model (SPCAM) and the second with a near-global cloud-resolving model (GCRM). Additionally, even though the SPCAM simulation has a warmer climate than the cloud-resolving model, both neural networks predict stronger heating/drying in moist and unstable environments, which is consistent with observations. Moreover, the spectral analysis can predict that instability occurs when GCMs are coupled to networks that support gravity waves that are unstable and have phase speeds larger than 5 m s -1 . In contrast, standing unstable modes do not cause catastrophic instability. Using these tools, differences between the SPCAM-trained versus GCRM-trained neural networks are analyzed, and strategies to incrementally improve both of their coupled online performance unveiled.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Ice Particle and Aggregate Simulator (IPAS). Part III: Verification and Analysis of Ice–Aggregate and Aggregate–Aggregate Collection for Microphysical Parameterization

Abstract The Ice Particle and Aggregate Simulator (IPAS) is used to theoretically represent the aggregation process of ice crystals. Aggregates have a variety of formations based on initial ice particle size, shape, and falling orientation, all of which influence water phase partitioning. Aggregate dimensional properties and density changes are calculated for monomer–monomer (MON–MON), monomer–aggregate (MON–AGG), and aggregate–aggregate (AGG–AGG) collection to be used by ice-microphysical models for improvement in aggregation parameterizations. Aggregates are chosen from a database of 9 744 000 preformed combinations to be further collected (see Part II). AGG–AGG collection results in more extreme and a smaller range of aggregate aspect ratios than MON–AGG collection. A majority of aggregates are closer to prolate than oblate spheroids, regardless of collection type, except for quasi-horizontally oriented particles that have extreme aspect ratios to begin with. MON–AGG collection frequently results in an increase in density upon collection, whereas MON–MON and AGG–AGG collection almost always result in particle density decreases, with extreme reductions near 99% for MON–MON collection. MON–MON collection results in the greatest decreases in density but then quickly becomes unaffected by the addition of more monomers due to inherent size differences between monomers and aggregates. Finally, a holistic analysis to in situ observations of cloud particle images is presented. IPAS 2D aspect ratios surround a median value of 0.6 and closely follow that of previous studies while varying by no more than ≈12% on average from observed aggregates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Empirical Estimation of Shortest Route Length along U.S. Interstate Highways Based on Great Circle Distance

In this study, 98 regression models were specified for easily estimating shortest distances based on great circle distances along the U.S. interstate highways nationwide and for each of the continental 48 states. This allows transportation professionals to quickly generate distance, or even distance matrix, without expending significant efforts on complicated shortest path calculations. For simple usage by all professionals, all models are present in the simple linear regression form. Only one explanatory variable, the great circle distance, is considered to calculate the route distance. For each geographic scope (i.e., the national or one of the states), two different models were considered, with and without the intercept. Based on the adjusted R-squared, it was observed that models without intercepts generally have better fitness. Additionally, all these models generally have good fitness with the linear regression relationship between the great circle distance and route distance. At the state level, significant variations in the slope coefficients between the state-level models were also observed. Furthermore, a preliminary analysis of the effect of highway density on this variation was conducted.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Rapid simulations of hyperspectral near-field images of three-dimensional heterogeneous surfaces – part II

The modeling of the near-field interaction in the scattering-type scanning near-field optical microscope (s-SNOM) is rapidly advancing, although an accurate yet versatile modeling framework that can be easily adapted to various complex situations is still lacking. In this work, we propose a time-efficient numerical scheme in the quasi-electrostatic limit to capture the tip-sample interaction in the near field. This method considers an extended tip geometry, which is a significant advantage compared to the previously reported method based on the point-dipole approximation. Using this formalism, we investigate, among others, nontrivial questions such as uniaxial and biaxial anisotropy in the near-field interaction, the relationship between various experimental parameters (e.g. tip radius, tapping amplitude, etc.), and the tip-dependent spatial resolution. The demonstrated method further sheds light on the understanding of the contrast mechanism in s-SNOM imaging and spectroscopy, while also representing a valuable platform for future quantitative analysis of the experimental observations.

Chen, Xinzhong (ORCID:0000000261033848)↗
DOE OSTI2022

Model: Year-Long Reforecast, Forecast 02, Domain 01

The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the physics associated with the wind flow in and around the wind plant across a range of temporal and spatial scales, which will be gained through WFIP2’s observational field study and analysis.

17 WIND ENERGY↗
DOE OSTI2021

wfip2.model/realtime.hrrr_esrl.graphics.01 (Model: Real Time)

The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the physics associated with the wind flow in and around the wind plant across a range of temporal and spatial scales, which will be gained through WFIP2’s observational field study and analysis.

17 WIND ENERGY↗
DOE OSTI2021

wfip2.model/realtime.hrrr_wfip2.graphics.02 (Model: Real Time)

The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the physics associated with the wind flow in and around the wind plant across a range of temporal and spatial scales, which will be gained through WFIP2’s observational field study and analysis.

17 WIND ENERGY↗
DOE OSTI2021

wfip2.model/realtime.hrrr_esrl.icbc.01 (Model: Real Time)

The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the physics associated with the wind flow in and around the wind plant across a range of temporal and spatial scales, which will be gained through WFIP2’s observational field study and analysis.

17 WIND ENERGY↗
DOE OSTI2021

wfip2.model/realtime.hrrr_wfip2.icbc.02 (Model: Real Time)

The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the physics associated with the wind flow in and around the wind plant across a range of temporal and spatial scales, which will be gained through WFIP2’s observational field study and analysis.

17 WIND ENERGY↗