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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Landscape‐scale lidar analysis of aboveground biomass distribution in secondary Brazilian Atlantic Forest

Abstract Secondary forests account for more than half of tropical forests and represent a growing carbon sink, but rates of biomass accumulation vary by a factor of two or more even among plots in the same landscape. To better understand the drivers of this variability, we used airborne lidar to measure forest canopy height and estimate biomass over 4529 ha at Serra do Conduru Park in Southern Bahia, Brazil. We measured trees in 30 georeferenced field plots (0.25‐ha each) to estimate biomass using allometry. Then we estimated aboveground biomass density ( ABD ) across the lidar study area using a statistical model developed from our field plots. This model related the 95th percentile of the distribution of lidar return heights to ABD . We overlaid this map of ABD on a Landsat‐derived forest age map to determine rates of biomass accumulation. We found rapid initial biomass regeneration (~6 Mg/ha yr), which slowed as forests aged. We also observed high variability in both height and biomass across the landscape within forests of similar age. Nevertheless, a regression model that accounted for spatial autocorrelation and included forest age, slope, and distance to roads or open areas explained 62 and 77 percent of the landscape variation in ABD and canopy height, respectively. Thus, while there is high spatial heterogeneity in forest recovery, and the drivers of this heterogeneity warrant further investigation, we suggest that a relatively simple set of predictor variables is sufficient to explain the majority of variance in both height and ABD in this landscape.

Becknell, Justin M.↗
DOE OSTI2023

Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties–including data circularity–were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Crown damage and the mortality of tropical trees

Summary What causes individual tree death in tropical forests remains a major gap in our understanding of the biology of tropical trees and leads to significant uncertainty in predicting global carbon cycle dynamics. We measured individual characteristics (diameter at breast height, wood density, growth rate, crown illumination and crown form) and environmental conditions (soil fertility and habitat suitability) for 26 425 trees ≥ 10 cm diameter at breast height belonging to 416 species in a 52‐ha plot in Lambir Hills National Park, Malaysia. We used structural equation models to investigate the relationships among the different factors and tree mortality. Crown form (a proxy for mechanical damage and other stresses) and prior growth were the two most important factors related to mortality. The effect of all variables on mortality (except habitat suitability) was substantially greater than expected by chance. Tree death is the result of interactions between factors, including direct and indirect effects. Crown form/damage and prior growth mediated most of the effect of tree size, wood density, fertility and habitat suitability on mortality. Large‐scale assessment of crown form or status may result in improved prediction of individual tree death at the landscape scale.

Arellano, Gabriel↗
DOE OSTI2024

Organic carbon feedbacks to soil structure in Profundihumic and Haplic Ferralsols in Campinas, Sao Paulo, Brazil

Increasing soil organic matter content coincides with increasing soil porosity and decreasing bulk density, but the mechanisms that lead to changes in soil structure are unclear. We quantified and compared soil characteristics across two contrasting soils (heavily weathered ferralsols in Brazil) to clarify the effects of organic matter content on soil porosity. We found that high organic matter content fosters higher biologic activity, including root growth and animal burrowing, which in turn increase soil porosity and decreases bulk density.This dataset includes soil physical, morophological, and chemical variables from 6 soil profiles were sampled in Campinas, Sa ̃o Paulo state, southeastern Brazil to 1 m depth. Sites are regenerated mixed savanna and rainforest in the protected area of Viracopos Airport in Campinas, lightly grazed by cattle.This dataset includes soil color, bulk density, texture (percent sand, silt, clay, and coarse fragments as well as class), soil pH, cation exchange capacity, C stock, C concentration, N stock, N concentration, delta 13C, Delta 14C, and soil porosity in Excel and csv format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Build Rate Optimization for Powder Bed Fusion

The authors previously proposed a geometrically based model to predict the volume fraction of lack-of-fusion porosity in parts produced by powder bed fusion. To test this model, AlSi10Mg cubes with varying hatch spacing and layer thickness were printed in this work. Bulk densities of samples were measured with the Archimedes method and agree well with model predictions. The model was also validated by results from the literature on additively manufactured PA-12 polymer parts. Quantitative prediction of conditions that lead to part porosity allows considerable improvement in the volumetric build rate, compared with the default processing parameters provided by the equipment supplier. Nearly fully dense AlSi10Mg parts (> 99.5% dense) were fabricated with a build rate double that for standard conditions. Some melt-pool variability and large changes in hatch rotation angle do not affect the overall volume fraction of residual porosity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Disparities in the air quality monitoring stations and PM₂.₅ in Chicago’s air quality landscape

Fine particulate matter (PM₂.₅) poses significant public and environmental health risks in urban areas. Chicago’s dense industry and traffic create variable air quality, yet monitoring is unevenly distributed, resulting in undersampling of air quality data in some city areas. This study applied a hybrid approach using GIS-based kernel density mapping, interpolation modeling (IDW, Spline, Kriging) of USEPA monitoring data, multi-scale temporal trend analyses (hourly to annual), and ESDA. Accordingly, the density surface showed that monitors are concentrated in the affluent north, northwest, and southwest sides of Chicago (up to ~ 0.07 stations per sq mile), while the south and southeast regions, with predominantly minority communities, have virtually no coverage. Overall, citywide coverage is minimal (~ 4–5 monitors total; ~0.02 per sq mile; ≈1 per 600,000 residents). Temporal analyses showed that the city’s mean annual PM₂.₅ (~ 10.8 µg/m³) exceeds USEPA/WHO standards (9 µg/m³), with summer means (~ 17.1 µg/m³) significantly higher than other seasons. Diurnally, a clear pattern was observed, with PM₂.₅ concentrations peaking overnight (00:00–03:00) and during the morning rush hours, and dipping during midday to late afternoon. Spatial distribution of PM₂.₅ identified hotspots near O’Hare Airport, the downtown Loop area, and south-side neighborhoods, contrasting with lower concentrations on the north side, revealing Chicago’s socioeconomic divides and resulting environmental inequities. The findings underscore the need for expanded monitoring and targeted interventions in under-monitored, high-pollution communities to advance equitable community health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking

In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) can not fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, the modeling error PDF by the tradional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. Furthermore, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.

Modelling↗
DOE OSTI2024

Technique for an improved and time-resolved carbon areal density measurement with a single channel diagnostic for inertial confinement fusion

Measurement of the areal density and velocity of the carbon ablator shell during peak burn in inertial confinement fusion give powerful information on the state of the ablator and where in the trajectory of implosion it reaches peak burn. Detailed comparison of the absolute densities and velocities of the carbon in implosions has been prevented by the limited ability to resolve shot-to-shot variation within a shot series or within a campaign. Here, a new approach using a single, ultra fast (~10 ps) gamma ray channel can massively reduce uncertainties and will provide insights on improvements to target and drive variables. Small improvements in these experimental design parameters may result in much greater yields.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Reduction of π–Expanded Cyclooctatetraene with Lithium: Stabilization of the Tetra–Anion through Internal Li + Coordination

The chemical reduction of a π-expanded polycyclic framework comprising a cyclooctatetraene moiety, octaphenyltetrabenzocyclooctatetraene, with lithium metal readily affords the corresponding tetra-anion instead of the expected aromatic dianion. As revealed by X-ray crystallography, the highly contorted tetra-anion is stabilized by coordination of two internally bound Li + , while two external cations remain solvent separated. The variable-temperature 7 Li NMR spectra in THF confirm the presence of three types of Li + ions and clearly differentiate internal binding, consistent with the crystal structure. Density-functional theory calculations suggest that the formation of the highly charged tetra-reduced carbanion is stabilized through Li + coordination under the applied experimental conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Explaining Snowball-in-Hell Phenomena in Heavy-Ion Collisions Using a Novel Thermodynamic Variable

A loosely bound hadronic molecule produced by a relativistic heavy-ion collision has been described as a “snowball in hell” since it emerges from a hadron resonance gas whose temperature is orders of magnitude larger than the binding energy of the molecule. This remarkable phenomenon can be explained in terms of a novel thermodynamic variable called the “contact” that is conjugate to the binding momentum of the molecule. The production rate of the molecule can be expressed in terms of the contact density at the kinetic freeze-out of the hadron resonance gas. It approaches a nonzero limit as the binding energy goes to 0.

Relativistic heavy-ion collisions↗
DOE OSTI2020

Summary of Expedited Results from Samples Supporting Tank Closure Cesium Removal (TCCR) Batch 3

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal (TCCR) process to remove 137 Cs from tank waste supernate using an ion exchange process. As part of that process, Savannah River National Laboratory (SRNL) receives and analyzes samples in support of the qualification of each batch to be processed. SRNL recently received supernate samples retrieved from Tank 10H as well as in-tank batch contact samples for characterization in support of qualifying Batch 3 for processing through the TCCR unit. SRNL received and characterized a set of dip samples collected from Tank 10H (one surface and one variable depth sample). No solids were observed in either sample and therefore the samples were combined, and a suite of analyses were performed on the composite sample. The density of the combined sample was 1.174 g/mL (0.18 %RSD), which was consistent with the measured sodium concentration of 3.54 M (0.08 %RSD). The 137Cs activity in the sample was 4.75E+07 dpm/mL (4.28 %RSD) and the total Cs concentration was calculated to be 1.54 mg/L (1.16E-05 M). The in-tank batch contact samples consist of 0.1 g of crystalline silicotitanate (CST) contained within a teabag device. Duplicate samples were submerged in Tank 10H supernate for a period of about 13 days, after which time they were retrieved and transferred to SRNL for analysis. At SRNL the CST was rinsed to remove excess salt solution and the CST was then air dried before being digested for analysis. Results of the analysis indicated a 137 Cs loading of 3.66E+10 ± 1.40E+09 dpm/g or 16.5 ± 0.63 Ci/kg CST . This value represents a bounding upper limit as it includes the addition of two sigma uncertainty from replicate analysis of the individual teabag samples as well as the addition of the small amount of 137 Cs activity measured in the rinse solutions. The above values are based on the air-dried mass of CST. Correcting to the true dry mass using a F-factor of 0.8191 results in a maximum loading of 20.2 ± 0.77 Ci/kg CST .

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Duke Forest FACE (FACTS-I): Plant and Soil Response Data

This dataset describing the responses of plant and soil pools and fluxes to elevated atmospheric CO2 concentration and increased nitrogen supply was collected from Duke Forest Free Air CO2 Enrichment (FACE) – Forest-Atmosphere Carbon Transfer and Storage (FACTS-I) experiment from 1996 to 2012. The dataset includes data files for allometry (diameter at breast height, tree height, and height to live crown base), leaf area index, biomass (stem, branch, foliage, and root biomass, tree density, and basal area), net primary productivity (stem, branch, foliage, reproductive, and coarse root NPP), sap flux density, soil CO2 efflux, and stem temperature. Data files were formatted as .csv (Microsoft Excel or other spreadsheet programs can be used to read the format) and file descriptions, including variable name, unit, and data range, can be found in ‘FileDescription_[data_name].txt’ files. The Duke FACE experiment was in a loblolly pine (Pinus taeda L.) plantation established in 1983. Naturally regenerated broadleaved species including sweetgum (Liquidambar styraciflua L.) and tulip poplar (Liriodendron tulipifera L.), mostly in the overstory, and winged elm (Ulmus alata Michx.) and red maple (Acer rubrum L.) were common in the understory. The FACE experiment commenced with two plots (plots 7-8) in 1994 (Oren et al. 2001), with six additional plots (plots 1-6) coming online on 27 August 1996. CO2 enrichment was terminated on 31 October 2010 and post-enrichment data collection continued through 2012. Complete fertilization was applied annually to half of plots 7-8 from 1998 to 2004. The nutrient addition experiment expanded to half of plots 1-6 with a common protocol of N-fertilization in 2005 and continued until 2012. The levels of treatment in this dataset were expressed as ambient CO2 (AMB) or elevated CO2 (ELE) for CO2 treatment and control soil (CONT) or fertilized soil (FERT) for N treatment, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Detection of Outliers in LiDAR Data Acquired by Multiple Platforms over Sorghum and Maize

High-resolution point cloud data acquired with a laser scanner from any platform contain random noise and outliers. Therefore, outlier detection in LiDAR data is often necessary prior to analysis. Applications in agriculture are particularly challenging, as there is typically no prior knowledge of the statistical distribution of points, plant complexity, and local point densities, which are crop-dependent. The goals of this study were first to investigate approaches to minimize the impact of outliers on LiDAR acquired over agricultural row crops, and specifically for sorghum and maize breeding experiments, by an unmanned aerial vehicle (UAV) and a wheel-based ground platform; second, to evaluate the impact of existing outliers in the datasets on leaf area index (LAI) prediction using LiDAR data. Two methods were investigated to detect and remove the outliers from the plant datasets. The first was based on surface fitting to noisy point cloud data via normal and curvature estimation in a local neighborhood. The second utilized the PointCleanNet deep learning framework. Both methods were applied to individual plants and field-based datasets. To evaluate the method, an F-score was calculated for synthetic data in the controlled conditions, and LAI, the variable being predicted, was computed both before and after outlier removal for both scenarios. Results indicate that the deep learning method for outlier detection is more robust than the geometric approach to changes in point densities, level of noise, and shapes. The prediction of LAI was also improved for the wheel-based vehicle data based on the coefficient of determination (R2) and the root mean squared error (RMSE) of the residuals before and after the removal of outliers.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Analysis of Quasi-periodic Oscillations and Time Lag in Ultraluminous X-Ray Sources with XMM-Newton

We investigated the power density spectrum (PDS) and time lag of ultraluminous X-ray sources (ULXs) observed by XMM-Newton . We determined the PDSs for each ULX and found that five of them show intrinsic variability due to obvious quasi-periodic oscillations (QPOs) of mHz–1 Hz, consistent with previous reports. We further investigated these five ULXs to determine their possible time lag. The ULX QPOs exhibit a soft time lag that is linearly related to the QPO frequency. We discuss the likelihood of the ULX QPOs being type-C QPO analogs, and the time lag models. The ULXs might harbor intermediate-mass black holes if their QPOs are type-C QPO analogs. We suggest that the soft lag and the linearity may be due to reverberation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Atmospheric Dynamics and the Variable Transit of KELT-9 b

We present a spectrally and temporally resolved detection of the optical Mg i triplet at 7.8σ in the extended atmosphere of the ultra-hot Jupiter KELT-9 b, adding to the list of detected metal species in the hottest gas giant currently known. Constraints are placed on the density and radial extent of the excited hydrogen envelope using simultaneous observations of Hα and Hβ under the assumption of a spherically symmetric atmosphere. We find that planetary rotational broadening of v{sub rot}=8.2{sub −0.7}{sup +0.6} km s{sup −1} is necessary to reproduce the Balmer line transmission profile shapes, where the model including rotation is strongly preferred over the non-rotating model using a Bayesian information criterion comparison. The time series of both metal line and hydrogen absorption show remarkable structure, suggesting that the atmosphere observed during this transit is dynamic rather than static. We detect a relative emission feature near the end of the transit which exhibits a P-Cygni-like shape, evidence of material moving at ≈50–100 km s{sup −1} away from the planet. We hypothesize that the in-transit variability and subsequent P-Cygni-like profiles are due to a flaring event that caused the atmosphere to expand, resulting in unbound material being accelerated to high speeds by stellar radiation pressure. Further spectroscopic transit observations will help establish the frequency of such events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Assessment of long-term spatio-temporal radiofrequency electromagnetic field exposure

Highlights: • A year's worth of RF-EMF data is collected in an urban sensor network is analysed. • A full spatio-temporal model of the RF-EMF exposure in the study area is built. • Short-term variations of the RF-EMF exposure are collected in temporal profiles. • Models using data collected at different instants are improved by adjusting for time. As both the environment and telecommunications networks are inherently dynamic, our exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) at an arbitrary location is not at all constant in time. In this study, more than a year's worth of measurement data collected in a fixed low-cost exposimeter network distributed over an urban environment was analysed and used to build, for the first time, a full spatio-temporal surrogate model of outdoor exposure to downlink Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) signals. Though no global trend was discovered over the measuring period, the difference in measured exposure between two instances could reach up to 42 dB (a factor 12,000 in power density). Furthermore, it was found that, taking into account the hour and day of the measurement, the accuracy of the surrogate model in the area under study was improved by up to 50% compared to models that neglect the daily temporal variability of the RF signals. However, further study is required to assess the extent to which the results obtained in the considered environment can be extrapolated to other geographic locations.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

The oscillatory anisotropy in the spatially flat cosmological models

Highlights: • Relations among asymptotic anisotropy and matter content. • A new scheme for obtaining physically motivated exact solutions. • The process of isotropization/anisotropization in cosmology. • The conversion among the anisotropy and the energy density into one another. In this manuscript, we investigate the oscillatory behaviour of the anisotropy in the diagonal Bianchi-I spacetimes. Our starting point is a simplification of Einstein’s equations using only observable or physical variables. As a consequence, we are able to: (a) Prove general results concerning the existence of oscillations of the anisotropy in the primordial and the late-time universe. For instance, in the expanding scenario, we show that a past weakly mixmaster behaviour (oscillations as we approach the Kasner solutions) might appear even with no violation of the usual energy conditions, while in the future, the pulsation (oscillations around isotropic solutions) seems to be most favoured; (b) Determine a large scheme for deriving classes of physically motivated exact solutions, and we give some (including the general barotropic perfect fluid and the magnetic one); (c) Understand the physical conditions for the occurrence of the isotropization or anisotropization during the cosmological evolution; (d) Understand how anisotropy and energy density are converted one into another. In particular, we call attention to the presence of a residue in the energy density in a late-time isotropic universe coming from its past anisotropic behaviour.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The effect of polymer grafting on the mechanical properties of PEG-grafted cellulose nanocrystals in poly(lactic acid)

Poly(lactic acid) (PLA) is a commercially available bio-based polymer that is a potential alternative to many commodity petrochemical-based polymers. However, PLA's thermomechanical properties limit its use in many applications. Incorporating polymer-grafted cellulose nanocrystals (CNCs) is one potential route to improving these mechanical properties. One key challenge in using these polymer-grafted nanoparticles is to understand which variables associated with polymer grafting are most important for improving composite properties. In this work, poly(ethylene glycol)-grafted CNCs are used to study the effects of polymer grafting density and molecular weight on the properties of PLA composites. All CNC nanofillers are found to reinforce PLA above the glass transition temperature, but non-grafted CNCs and CNCs grafted with short PEG chains (<2 kg mol –1 ) are found to cause significant embrittlement, generally resulting in less than 3% elongation-at-break. By grafting higher molecular weight PEG (10 kg mol –1 ) onto the CNCs at a grafting density where the polymer chains are predicted to be in the semi-dilute polymer brush conformation (~0.1 chains nm –2 ), embrittlement can be avoided.

36 MATERIALS SCIENCE↗