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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Assessing outdoor air quality and public health impact attributable to residential black carbon emissions in rural China

Black carbon (BC) is a significant component of particulate matter (PM) that relates to air pollution, climate forcing, and further implications for public health. BC is predominantly released from the combustion of solid fuels. Combustion of low-quality fuels in rural China may induce severe respiratory and cardiopulmonary health outcomes for residents, which have however been inadequately assessed. One major reason for the limited understanding is the lack of a high-resolution inventory. An improved method of estimating the BC-associated public health burden is needed. This work quantified premature mortalities due to residential BC emissions in rural China. Domestic BC emissions at 1×1 km resolution were compiled based on previous field investigation, which were further configured for air quality simulation. A chemistry transport model, WRF–CMAQ v5.2, was employed for simulating BC concentrations. The consequent premature mortalities were quantified by a BC-specific concentration-response function (CRF) derived from an epidemiological study. Results show that residential combustion of solid fuel in rural China emitted 648.0 Gg (95%CI: 361.0–965.9) BC in 2014, after dispersion, accounting for 51.8% of annual mean ground-level BC concentration in China. Such impact was most severe in North and Northeast China, and the Sichuan Basin. The further investigation estimated 171,000 (95%CI: 69,000–387,000) premature mortalities that were attributable to exposure to rural residential BC. These findings reveal the major contribution of rural residential BC emissions to air pollution formation and public health impacts. Our findings are anticipated to provide useful information for enacting the next-stage environmental strategy for the residential sector in China.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

A novel approach for large-scale wind energy potential assessment

Increasing wind energy generation is central to grid decarbonization, yet methods to estimate wind energy potential are not standardized, leading to inconsistencies and even skewed results. This study aims to improve the fidelity of wind energy potential estimates through an approach that integrates geospatial analysis and machine learning (i.e., Gaussian process regression). We demonstrate this approach to assess the spatial distribution of wind energy capacity potential in the Contiguous United States (CONUS). We find that the capacity-based power density ranges from 1.70 MW/km2 (25th percentile) to 3.88 MW/km2 (75th percentile) for existing wind farms in the CONUS. The value is lower in agricultural areas (2.73 ± 0.02 MW/km2, mean ± 95 % confidence interval) and higher in other land cover types (3.30 ± 0.03 MW/km2). Notably, advancements in turbine manufacturing could reduce power density in areas with lower wind speeds by adopting low specific-power turbines, but improve power density in areas with higher wind speeds (>8.35 m/s at 120m above the ground), highlighting opportunities for repowering existing wind farms. Wind energy potential is shaped by wind resource quality and is regionally characterized by land cover and physical conditions, revealing significant capacity potential in the Great Plains and Upper Texas. The results indicate that areas previously identified as hot spots using existing approaches (e.g., the west of the Rocky Mountains) may have a limited capacity potential due to low wind resource quality. Improvements in methodology and capacity potential estimates in this study could serve as a new basis for future energy systems analysis and planning.

Dai, Tao↗
DOE OSTI2017

Photovoltaic system derived data for determining the solar resource and for modeling the performance of other photovoltaic systems

Using performance data from some of the millions of installed photovoltaic (PV) modules with micro-inverters may afford the opportunity to provide ground-based solar resource data critical for developing PV projects. Here, a method was developed to back-solve for the direct normal irradiance (DNI) and the diffuse horizontal irradiance (DHI) from the measured ac power of south-facing PV module/micro-inverter systems. The method was validated using one year of irradiance and PV performance measurements for five PV systems, each with a different tilt/azimuth orientation, and located in Golden, Colorado. Compared to using a measured global horizontal irradiance for PV performance model input, using the back-solved values of DNI and DHI only increased the range of mean bias deviations from measured values by 0.6% for the modeled annual averages of the global tilt irradiance and ac power for the five PV systems. Correcting for angle-of-incidence effects is an important feature of the method to prevent underestimating the solar resource and for modeling the performance of PV systems with more dissimilar PV module orientations. The results for the method were also shown more favorable than the results when using an existing power projection method for estimating the ac power.

14 SOLAR ENERGY↗
DOE OSTI2026

Absorption Correction for Reliable Pair Distribution Functions from Low Energy X-ray Sources

This paper explores the development and testing of a simple absorption correction model for processing powder X-ray diffraction data from Debye−Scherrer geometry laboratory X-ray experiments. This may be used as a preprocessing step before using PDFGETX3 to obtain reliable pair distribution functions (PDFs). Various experimental and theoretical methods for estimating μR were explored, and the most appropriate μR values for correction were identified for different capillary diameters and X-ray beam sizes. We identify operational ranges of μR where a reasonable signal-to-noise ratio is possible after correction. A user-friendly software package, DIFFPY.LABPDFPROC, is presented that can help estimate μR and perform absorption corrections with a rapid calculation for efficient processing.

Absorption↗
DOE OSTI2020

Predicting the Phase Stability of Multicomponent High-Entropy Compounds

A generic method to estimate the relative feasibility of formation of high-entropy compounds in a single phase, directly from first principles, is developed. As a first step, the relative formation abilities of 56 multicomponent, AO, oxides were evaluated. These were constructed from five cation combinations chosen from A = {Ca, Co, Cu, Fe, Mg, Mn, Ni, Zn}. Candidates for multicomponent oxides are predicted from descriptors related to the enthalpy and configurational entropy obtained from the mixing enthalpies of two-component oxides. The utility of this approach is evaluated by comparing the predicted combinations with the experimentally realized entropy-stabilized oxide, (MgCoCuNiZn)O. In the second step, Monte Carlo simulations are utilized to investigate the phase composition and local ionic segregation as a function of temperature. This approach allows for the evaluation of potential secondary phases, thereby making realistic predictions of novel multicomponent compounds that can be synthesized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Novel Technological Approach To Enhance Methane Recovery from Class 2 Hydrate Deposits by Employing CO 2 Injection

Class 2 hydrate accumulations are characterized by the presence of an aquifer underneath hydrate bearing sediment. Gas extraction from of these hydrate deposits is accompanied by release of large volumes of water that decreases gas production rates, imposes additional load on the lifting system and, as a result, degrades economical attractiveness of possible exploitation sites. Here, we study the enhanced methane production from Class 2 hydrate accumulations using the CO 2 -assisted technique in which the aquifer serves as a target zone for CO 2 injection. The heat release associated with the CO 2 hydrate formation and reduction of the aquifer’s permeability benefit the subsequent decomposition of the overlying methane hydrate. The new production technique includes three stages utilizing one vertical well, which serves as an injector during the first stage and as a producer in the third stage. First, the CO 2 is injected into the underlying aquifer, then the well is shut down and injected CO 2 is converted into hydrate during the second stage. In the third stage, decomposition of CH 4 hydrate is induced by the depressurization method to estimate gas production potential over 15 years. Lastly, the results reveal that methane production is increased together with simultaneous reduction of concomitant water production compared to production from the Class 2 reservoir using only conventional depressurization.

03 NATURAL GAS↗
DOE OSTI2024

Unlocking Solutions: Innovative Approaches to Identifying and Mitigating the Environmental Impacts of Undocumented Orphan Wells in the United States

In the United States, hundreds of thousands of undocumented orphan wells have been abandoned, leaving the burden of managing environmental hazards to governmental agencies or the public. These wells, a result of over a century of fossil fuel extraction without adequate regulation, lack basic information like location and depth, emit greenhouse gases, and leak toxic substances into groundwater. For most of these wells, basic information such as well location and depth is unknown or unverified. Addressing this issue necessitates innovative and interdisciplinary approaches for locating, characterizing, and mitigating their environmental impacts. Our survey of the United States revealed the need for tools to identify well locations and assess conditions, prompting the development of technologies including machine learning to automatically extract information from old records (95%+ accuracy), remote sensing technologies like aero-magnetometers to find buried wells, and cost-effective methods for estimating methane emissions. Notably, fixed-wing drones equipped with magnetometers have emerged as cost-effective and efficient for discovering unknown wells, offering advantages over helicopters and quadcopters. Efforts also involved leveraging local knowledge through outreach to state and tribal governments as well as citizen science initiatives. These initiatives aim to significantly contribute to environmental sustainability by reducing greenhouse gases and improving air and water quality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Rate/Concentration Kinetic Petals: A Transient Method to Examine the Interplay of Surface Reaction Processes

Transient pulse response experiments are used to construct rate/concentration (RC) kinetic dependencies—RC petals—and provide a new method to distinguish the timing and interplay of adsorption, surface reaction, and product formation on complex (industrial) materials. A petal shape arises as the dynamic “reaction-diffusion” experiment forces the concentration and reaction rate to return to zero. In contrast to the typical steady-state “Langmuir-type” RC dependence, RC petals have two branches, which arise as a result of decoupled gas and surface concentrations in the non-steady-state regime. To demonstrate this approach, the characteristics of petal shapes using ammonia decomposition as a probe reaction are presented. Ammonia, hydrogen, and nitrogen transformation rates are compared on three simple materials: Fe, Co, and a bimetallic CoFe preparation when ammonia is pulsed at 550°C in a low-pressure diffusion reactor. All materials demonstrate a two-branch kinetic RC dependence for ammonia adsorption, and rate constants are quantified in the low-coverage regime. We found that H 2 and N 2 product formation was dependent on the concentration of surface intermediates for all materials with one exception: for Co, an additional fast hydrogen generation process was observed; the rate of which coincided with ammonia adsorption. Nitrogen generation was only significant for CoFe and Co and on the CoFe catalyst, a self-inhibition property was observed. A method for estimating the number of active sites based on the RC petals is presented and was applied to the Fe and CoFe samples. The surface coverage and rate of formation/conversion of surface intermediates are interpreted from the examination of shape characteristics of the RC petals for each material.

36 MATERIALS SCIENCE↗
DOE OSTI2021

How Fast Can a Li-Ion Battery Be Charged? Determination of Limiting Fast Charging Conditions

Fast-charge protocols that prevent lithium plating are needed to extend the life span of lithium-ion batteries. Here, we describe a simple experimental method to estimate the minimum charging time below which it is simply impossible to avoid plating at a given temperature. We demonstrate that, by gauging and correcting the ohmic drop that is intrinsic to reference electrodes, the local potential at the anode surface can be reasonably approximated. This finer anode control enables the determination of the maximum average rate at which lithium deposition can be mitigated, establishing realistic boundaries that can inform the development of advanced charging protocols.

25 ENERGY STORAGE↗
DOE OSTI2017

Chemical Potential of Metal Atoms in Supported Nanoparticles: Dependence upon Particle Size and Support

Metal nanoparticles supported on oxide surfaces form the basis for many industrial catalysts and promise to play an ever-increasing role in future energy and environmental technologies. The chemical potential (μ) of the metal atoms in these particles depends strongly on particle size and support and is an important factor that determines their catalytic properties, including their binding strengths to adsorbed reaction intermediates and their long-term stability against sintering. We present here a method for estimating this chemical potential as a function of particle size for different metal/oxide combinations. We show that this chemical potential for late transition metals is well approximated for a particle of diameter D by μ( D ) = [(3γ m – E adh )(1 + D o / D )](2 V m / D ), where γ m is the surface energy of the bulk metal, E adh is the adhesion energy at the bulk metal/oxide interface, and D o is ~1.5 nm, and V m is the molar volume of the bulk metal. We further show that E adh increases with (1) increasing heat of formation of the most stable oxide of the metal from metal gas atoms plus O 2 (gas) per mole of metal atoms, (2) decreasing enthalpy of reduction of the oxide to its next lower oxidation state plus O 2 (gas), per mole of oxygen atoms, and (3) increasing density of surface oxygen atoms on the oxide surface. The linear scaling of E adh with these properties allows estimations of E adh for a variety of metal/oxide combinations. Using this E adh estimate in the above equation with known values for γ m allows estimates of metal chemical potential versus particle size for late transition metals on various oxide supports. WE conclude this will improve our ability to understand structure–property relations in catalysis and design better catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Temporal Dynamics of Aerodynamic Canopy Height Derived From Eddy Covariance Momentum Flux Data Across North American Flux Networks

Aerodynamic canopy height ( h a ) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate h a from data are limited. This synthesis evaluates the applicability and robustness of the calculation of h a from eddy covariance momentum-flux data. At 69 forest sites, annual h a robustly predicted site-to-site and year-to-year differences in canopy heights ( R 2 = 0.88, 111 site-years). At 23 cropland/grassland sites, weekly h a successfully captured the dynamics of vegetation canopies over growing seasons ( R 2 > 0.70 in 74 site-years). Our results demonstrate the potential of flux-derived h a determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying h a derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Planning for electric vehicle needs by coupling charging profiles with urban mobility

The rising adoption of plug-in electric vehicles (PEVs) leads to the temporal alignment of their electricity and mobility demands. However, mobility demand has not yet been considered in electricity planning and management. Here, we present a method to estimate individual mobility of PEV drivers at fine temporal and spatial resolution, by integrating three unique datasets of mobile phone activity of 1.39 million Bay Area residents, census data and the PEV drivers survey data. Through coupling the uncovered patterns of PEV mobility with the charging activity of PEVs in 580,000 session profiles obtained in the same region, we recommend changes in PEV charging times of commuters at their work stations and shave the pronounced peak in power demand. Informed by the tariff of electricity, we calculate the monetary gains to incentivize the adoption of the recommendations. Furthermore, these results open avenues for planning for the future of coupled transportation and electricity needs using personalized data.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Comparing storm resolving models and climates via unsupervised machine learning

Global storm-resolving models (GSRMs) have gained widespread interest because of the unprecedented detail with which they resolve the global climate. However, it remains difficult to quantify objective differences in how GSRMs resolve complex atmospheric formations. This lack of comprehensive tools for comparing model similarities is a problem in many disparate fields that involve simulation tools for complex data. To address this challenge we develop methods to estimate distributional distances based on both nonlinear dimensionality reduction and vector quantization. Our approach automatically learns physically meaningful notions of similarity from low-dimensional latent data representations that the different models produce. This enables an intercomparison of nine GSRMs based on their high-dimensional simulation data (2D vertical velocity snapshots) and reveals that only six are similar in their representation of atmospheric dynamics. Furthermore, we uncover signatures of the convective response to global warming in a fully unsupervised way. Our study provides a path toward evaluating future high-resolution simulation data more objectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Application of saturation absorption spectroscopy to study the hyperfine structure of 235U and accurate 235U/238U isotope ratio determinations at 861.031 nm

The uranium transition 5f 3 6d7s 2 ( 5 L 6 ) → 5f 3 7s 2 7p ( 5 K 5 ) at 861.031 nm was studied using saturation absorption spectroscopy. The hyperfine structure of the 235 U isotope was determined by measuring the Doppler-suppressed absorption spectrum, and the hyperfine structure constants were obtained by employing transition-specific line strength theory and spectral fitting. The magnetic-dipole and electric-quadrupole constants were determined to be A = -3.2887 ± 0.1957 mK and B = 31.8712 ± 8.0789 mK for the upper state 5f 3 7s 2 7p ( 5 K 5 ). A theoretical calculation for the hyperfine structure constants of the 235 U isotope was also carried out by the relativistic configuration-interaction (RCI) method, and the obtained values were found to be in agreement with the measured values. In addition, the line profile of 238 U was experimentally investigated for different excitation intensities and modeled using the RCI method for estimating the transition probability and oscillator strength, with various residual broadening mechanisms considered beyond the radiative decay. Finally, we show that these results allow us to make improvements on the precision of spectral measurements using our previously developed technique for isotope ratio determinations in atomic beams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine learning predictions of diffusion in bulk and confined ionic liquids using simple descriptors

Ionic liquids have many intriguing properties and widespread applications such as separations and energy storage. However, ionic liquids are complex fluids and predicting their behavior is difficult, particularly in confined environments. We introduce fast and computationally efficient machine learning (ML) models that can predict diffusion coefficients and ionic conductivity of bulk and nanoconfined ionic liquids over a wide temperature range (350–500 K). The ML models are trained on molecular dynamics simulation data for 29 unique ionic liquids as bulk fluids and confined in graphite slit pores. This model is based on simple physical descriptors of the cations and anions such as molecular weight and surface area. Here, we also demonstrate that accurate results can be obtained using only descriptors derived from SMILES (simplified molecular-input line-entry system) codes for the ions with minimal computational effort. This offers a fast and efficient method for estimating diffusion and conductivity of nanoconfined ionic liquids at various temperatures without the need for expensive molecular dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

BeyondPlanck: V. Minimal ADC Corrections for Planck LFI

We describe the correction procedure for Analog-to-Digital Converter (ADC) differential non-linearities (DNL) adopted in the Bayesian end-to-end BEYONDPLANCK analysis framework. This method is nearly identical to that developed for the official Planck Low Frequency Instrument (LFI) Data Processing Center (DPC) analysis, and relies on the binned rms noise profile of each detector data stream. However, rather than building the correction profile directly from the raw rms profile, we first fit a Gaussian to each significant ADC-induced rms decrement, and then derive the corresponding correction model from this smooth model. The main advantage of this approach is that only samples which are significantly affected by ADC DNLs are corrected, as opposed to the DPC approach in which the correction is applied to all samples, filtering out signals not associated with ADC DNLs. The new corrections are only applied to data for which there is a clear detection of the non-linearities, and for which they perform at least comparably with the DPC corrections. Out of a total of 88 LFI data streams (sky and reference load for each of the 44 detectors) we apply the new minimal ADC corrections in 25 cases, and maintain the DPC corrections in 8 cases. All these corrections are applied to 44 or 70 GHz channels, while, as in previous analyses, none of the 30 GHz ADCs show significant evidence of non-linearity. By comparing the BEYONDPLANCK and DPC ADC correction methods, we estimate that the residual ADC uncertainty is about two orders of magnitude below the total noise of both the 44 and 70 GHz channels, and their impact on current cosmological parameter estimation is small. However, we also show that non-idealities in the ADC corrections can generate sharp stripes in the final frequency maps, and these could be important for future joint analyses with the Planck High Frequency Instrument (HFI), Wilkinson Microwave Anisotropy Probe (WMAP), or other datasets. We therefore conclude that, although the existing corrections are adequate for LFI-based cosmological parameter analysis, further work on LFI ADC corrections is still warranted.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Blanco DECam Bulge Survey (BDBS)

The Blanco DECam Bulge Survey (BDBS) has imaged more than 200 square degrees of the southern Galactic bulge, providing photometry in the ugrizy filters for ~250 million unique stars. The presence of a strong foreground disk population, along with complex reddening and extreme image crowding, has made it difficult to constrain the presence of young and intermediate age stars in the bulge population. We employed an accurate cross-match of BDBS with the latest data release (EDR3) from the Gaia mission, matching more than 140 million sources with BDBS photometry and Gaia EDR3 photometry and astrometry. We relied on Gaia EDR3 astrometry, without any photometric selection, to produce clean BDBS bulge colour-magnitude diagrams (CMDs). Gaia parallaxes were used to filter out bright foreground sources, and a Gaussian mixture model fit to Galactic proper motions could identify stars kinematically consistent with bulge membership. We applied this method to 127 different bulge fields of 1 deg 2 each, with |$\ell$| ≤ 9.5 ° and –9.5 ° ≤ b ≤ –2.5 °. The astrometric cleaning procedure removes the majority of blue stars in each field, especially near the Galactic plane, where the ratio of blue to red stars is .10%, increasing to values ~20% at higher Galactic latitudes. We rule out the presence of a widespread population of stars younger than 2 Gyr. The vast majority of blue stars brighter than the turnoff belong to the foreground population, according to their measured astrometry. We introduce the distance between the observed red giant branch bump and the red clump as a simple age proxy for the dominant population in the field, and we confirm the picture of a predominantly old bulge. Further work is needed to apply the method to estimate ages to fields at higher latitudes, and to model the complex morphology of the Galactic bulge. We also produce transverse kinematic maps, recovering expected patterns related to the presence of the bar and of the X-shaped nature of the bulge.

79 ASTRONOMY AND ASTROPHYSICS↗