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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

THE RECENT STELLAR ARCHEOLOGY OF M31-THE NEAREST RED DISK GALAXY

We examine the star-forming history of the M31 disk during the past few hundred Myr. The luminosity functions (LFs) of main-sequence stars at distances R{sub GC} > 21 kpc (i.e., >4 disk scale lengths) are matched by models that assume a constant star formation rate (SFR). However, at smaller R{sub GC} the LFs suggest that during the past {approx}10 Myr the SFR was 2-3 times higher than during the preceding {approx}100 Myr. The rings of cool gas that harbor a significant fraction of the current star-forming activity are traced by stars with ages {approx}100 Myr, indicating that (1) these structures have ages of at least 100 Myr and (2) stars in these structures do not follow the same relation between age and random velocity as their counterparts throughout the disks of other spiral galaxies, probably due to the inherently narrow orbital angular momentum distribution of the giant molecular clouds in these structures. The distribution of evolved red stars is not azimuthally symmetric, in the sense that the projected density along the northeast segment of the major axis is roughly twice that on the opposite side of the galaxy. The northeast arm of the major axis thus appears to be a fossil star-forming area that dates to intermediate epochs. Such a structure may be the consequence of interactions with a companion galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A recyclable self-healing composite with advanced sensing property

Polymer-based composites frequently encounter damage, often lurking beneath the surface and proving challenges to their early detection and repair. While material-based sensors show promise for encoding self-sensing properties within these composites, their in situ healing and reprocessability remain significant challenges. Therefore, the overarching goal of this study is the creation of a reprocessable polymeric composite encoded with self-healing attributes and the ability to autonomously sense damage. At the core of this innovation are vitrimers, a polymeric material characterized by a covalently adaptive dynamic network responsive to external factors such as heat. They combine thermoset-like resilience with thermoplastic-like flowability on demand under external stimuli. We nanoengineer a polyester-based vitrimeric polymer by incorporating piezoresistive carbon nanotubes (CNTs) as reinforcing elements that not only enhance its mechanical strength but also create a percolation network within the composite, thereby enabling piezoresistive self-sensing properties, all the while preserving the intrinsic self-healing capabilities offered by the vitrimeric matrix. The fabrication process of the composite involves a solvent-free in situ polymerization method that combines epoxy and anhydride-containing monomers with ~ 0.1 wt.% of CNTs. Once it was established that the introduction of CNTs into the polymeric matrix did not compromise the mechanical properties of the composite, their strain-sensing properties were characterized by applying cyclic loading while measuring their electrical resistance. Strikingly, CNT-enhanced vitrimer composite consistently retains its mechanical and sensing properties through repeated cycles of reshaping and reprocessing, underscoring its potential as a robust distributed strain sensor. This polyester-based vitrimeric composite is also easily recyclable without harsh chemical treatments. Preliminary findings from this study conclusively demonstrate that the bulk composite boasts both self-sensing capabilities and in situ detect healing properties, charting a promising course towards the development of a mechanically resilient multifunctional composite that seamlessly integrates selfsensing and healing capabilities.

Rohewal, Sargun Singh↗
DOE OSTI2021

Quantum Sensing for Energy Applications: Review and Perspective

On its revolutionary threshold, quantum sensing is creating potentially transformative opportunities to exploit intricate quantum mechanical phenomena in new ways to make ultrasensitive measurements of multiple parameters. Concurrently, growing interest in quantum sensing has created opportunities for its deployment to improve processes pertaining to energy production, distribution, and consumption. Safe and secure utilization of energy is dependent upon addressing challenges related to material stability and function, secure monitoring of infrastructure, and accuracy in detection and measurement. A summary of well-established and emerging quantum sensing materials and techniques, as well as the corresponding sensing platforms that have been developed for their deployment is provided here. Specifically, the enhancement of existing advanced sensing technologies with quantum methods and materials is focused on, enabling the realization of an unprecedented level of sensitivity, placing an emphasis on relevance to the energy industry. The review concludes with a discussion on high-value applications of quantum sensing to the energy sector, as well as remaining barriers to sensor deployment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Comparative Study of Hydrology and Icemelt in Three Nepal River Basins Using the Glacio-Hydrological Degree-Day Model (GDM) and Observations From the Advanced Scatterometer (ASCAT)

An assessment of the water supply and its seasonal and annual changes over the century in the High Mountain Asia (HMA) region is of increasing interest due to its potential impact on one-sixth of the global population. In order to understand the changing hydrology and snow and ice melt, we used remotely sensed Advanced Scatterometer (ASCAT) observations of glacier melt (GM) and a distributed and gridded Glacio-hydrological Degree-day Model (GDM) in three river basins: Tamor, Trishuli and Marsyangdi. The GDM-estimated contribution of snowmelt, icemelt, rainfall and baseflow in river flows is found to be most accurate in the Trishuli River basin, with Nash-Sutcliffe efficiency (NSE) between the estimated and observed discharges of 0.81 and volume differences of -0.5%, and reasonably accurate in the Tamor River basin, with NSE of 0.69 and volume difference of -7.51%. Similarly, NSE of 0.81 and volume difference of 4.64% in Marsyangdi River basin. We find strong similarities in the timing of glacier melting using the GDM and from observations from the ASCAT GM, determining the seasonal start of glacier melting to within 6 days on average. In all basins ASCAT GM observes melting at higher elevations relative to GDM, average of 5,328 m a.s.l. Systematic differences in glacier melting area determined by modeling and satellite observations indicate ASCAT may have suboptimal resolution, view geometry and/or polarimetry for delineating glacier melting at the process-scale in complex topography, especially in the ablation zone. This is the first step in examining the remote sensing products that could potentially be incorporated into hydrologic models to increase the accuracy of the hydrologic flow as well as the ability to estimate river discharge in other basins with limited data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

An HST/COS survey of the low-redshift intergalactic medium. I. Survey, methodology, and overall results

We use high-quality, medium-resolution Hubble Space Telescope/Cosmic Origins Spectrograph (HST/COS) observations of 82 UV-bright active galactic nuclei (AGNs) at redshifts z{sub AGN} < 0.85 to construct the largest survey of the low-redshift intergalactic medium (IGM) to date: 5138 individual extragalactic absorption lines in H i and 25 different metal-ion species grouped into 2611 distinct redshift systems at z{sub abs} < 0.75 covering total redshift pathlengths Δz{sub H i} = 21.7 and Δz{sub O vi} = 14.5. Our semi-automated line-finding and measurement technique renders the catalog as objectively defined as possible. The cumulative column density distribution of H i systems can be parametrized dN(>N)/dz = C{sub 14}(N/10{sup 14}cm{sup −2}){sup −(β−1)}, with C{sub 14} = 25 ± 1 and β = 1.65 ± 0.02. This distribution is seen to evolve both in amplitude, C{sub 14}∝(1+z){sup 2.3±0.1}, and slope β(z) = 1.75–0.31 z for z ≤ 0.47. We observe metal lines in 418 systems, and find that the fraction of IGM absorbers detected in metals is strongly dependent on N{sub HI}. The distribution of O vi absorbers appears to evolve in the same sense as the Lyα forest. We calculate contributions to Ω{sub b} from different components of the low-z IGM and determine the Lyα decrement as a function of redshift. IGM absorbers are analyzed via a two-point correlation function in velocity space. We find substantial clustering of H i absorbers on scales of Δv = 50–300 km s{sup −1} with no significant clustering at Δv ≳ 1000 km s{sup −1}. Splitting the sample into strong and weak absorbers, we see that most of the clustering occurs in strong, N{sub H i} ≳ 10{sup 13.5} cm{sup −2}, metal-bearing IGM systems. The full catalog of absorption lines and fully reduced spectra is available via the Mikulski Archive for Space Telescopes (MAST) as a high-level science product at http://archive.stsci.edu/prepds/igm/.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Spatiotemporal dynamics of wetted soils across a polar desert landscape

Liquid water is scarce across the landscape of the McMurdo Dry Valleys (MDV), Antarctica, a 3800 km 2 ice-free region, and is chiefly associated with soils that are adjacent to streams and lakes (i.e. wetted margins) during the annual thaw season. However, isolated wetted soils have been observed at locations distal from water bodies. The source of water for the isolated patches of wet soil is potentially generated by a combination of infiltration from melting snowpacks, melting of pore ice at the ice table, and melting of buried segregation ice formed during winter freezing. In this paper, high resolution remote sensing data gathered several times per summer in the MDV region were used to determine the spatial and temporal distribution of wet soils. The spatial consistency with which the wet soils occurred was assessed for the 2009–10 to 2011–12 summers. The remote sensing analyses reveal that cumulative area and number of wet soil patches varies among summers. The 2010–11 summer provided the most wetted soil area (10.21 km 2 ) and 2009–10 covered the least (5.38 km 2 ). Finally, these data suggest that wet soils are a significant component of the MDV cold desert land system and may become more prevalent as regional climate changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

High-Resolution PM2.5 Concentrations Estimation Based on Stacked Ensemble Learning Model Using Multi-Source Satellite TOA Data

Nepal has experienced severe fine particulate matter (PM2.5) pollution in recent years. However, few studies have focused on the distribution of PM2.5 and its variations in Nepal. Although many researchers have developed PM2.5 estimation models, these models have mainly focused on the kilometer scale, which cannot provide accurate spatial distribution of PM2.5 pollution. Based on Gaofen-1/6 and Landsat-8/9 satellite data, we developed a stacked ensemble learning model (named XGBLL) combined with meteorological data, ground PM2.5 concentrations, ground elevation, and population data. The model includes two layers: a XGBoost and Light GBM model in the first layer, and a linear regression model in the second layer. The accuracy of XGBLL model is better than that of a single model, and the fusion of multi-source satellite remote sensing data effectively improves the spatial coverage of PM2.5 concentrations. Besides, the spatial distribution of the daily mean PM2.5 concentrations in the Kathmandu region under different air conditions was analyzed. The validation results showed that the monthly averaged dataset was accurate (R2 = 0.80 and root mean square error = 7.07). In addition, compared to previous satellite PM2.5 datasets in Nepal, the dataset produced in this study achieved superior accuracy and spatial resolution.

Environmental Sciences & Ecology↗
DOE OSTI2020

Cyber‐physical system testbed for power system monitoring and wide‐area control verification

The electric power system is intrinsically a cyber‐physical system (CPS) with power flowing inthe physical system and information flowing in the cyber‐network. Testbeds arecrucial for understanding the cyber‐physical interactions and provideenvironments for prototyping novel applications. This study proposes afour‐layer architecture for CPS testbeds with emphases on communication networkemulation and networked physical components. A configurable software‐definednetwork is employed to bridge physical components with wide‐area applicationsfor closed‐loop control. In order to distribute physically coupled devices intomultiple software simulations, this study proposes a data broker setup based ona distributed messaging environment to achieve low‐latency data streaming. Thedecoupled design with data streaming allows for building testbed components asmodules and running them in a distributed manner. Case studies verify the databroker setup for low‐latency sensing and actuation, as well as the communicationemulation setup for the desired network latency. Also illustrated is a replayattack scenario using synchrophasors in the Western Electricity CoordinatingCouncil (WECC) 181‐bus system for demonstrating the closed‐loop cyber‐physicalsimulation capability of the testbed.

Cui, Hantao↗
DOE OSTI2013

Adaptive Control Parameters for Dispersal of Multi-Agent Mobile Ad Hoc Network (MANET) Swarms

A mobile ad hoc network is a collection of independent nodes that communicate wirelessly with one another. This paper investigates nodes that are swarm robots with communications and sensing capabilities. Each robot in the swarm may operate in a distributed and decentralized manner to achieve some goal. This paper presents a novel approach to dynamically adapting control parameters to achieve mesh configuration stability. The presented approach to robot interaction is based on spring force laws (attraction and repulsion laws) to create near-optimal mesh like configurations. In prior work, we presented the extended virtual spring mesh (EVSM) algorithm for the dispersion of robot swarms. This paper extends the EVSM framework by providing the first known study on the effects of adaptive versus static control parameters on robot swarm stability. The EVSM algorithm provides the following novelties: 1) improved performance with adaptive control parameters and 2) accelerated convergence with high formation effectiveness. Simulation results show that 120 robots reach convergence using adaptive control parameters more than twice as fast as with static control parameters in a multiple obstacle environment.

42 ENGINEERING↗
DOE OSTI2018

Prospective Environmental Analyses of Emerging Technology: A Critique, a Proposed Methodology, and a Case Study on Incremental Sheet Forming

Summary Prospective environmental assessment of emerging technology is necessary in order to inform designers of beneficial changes early in a technology's development, and policy makers looking to fund projects and nudge manufacturers toward the most sustainable application of a technology. Existing analyses often have shortcomings such as failing to consider the environmental impacts in all stages of a product's life cycle; implicitly assuming that the emerging technology will be cost‐effective wherever it is technically viable; and assuming optimistic application scenarios that discontinue long‐established trends in human behavior. In this article, we propose a new approach, complementary to the prospective and anticipatory life cycle assessment literature, addressing the above concerns and attempting to make sense of the large uncertainties inherent in such analyses by using distributions to model all the inputs. The paper focuses on emerging manufacturing technologies, such as incremental sheet forming (ISF), but the issues examined are also applicable to new end‐use products, such as autonomous vehicles. This paper makes use of approaches (such as Bass modeling and product cannibalization considerations) familiar to those in the business community who anticipate market diffusion of a new technology and the effect on existing technology sales. The proposed methodology is demonstrated by estimating the potential environmental impacts in the U.S. car industry by 2030 of an emerging double‐sided ISF process. Energy and cost models of ISF and drawing are used to estimate potential mean savings of around 100 TJ primary and 60 million U.S. dollars per year by 2030.

Cooper, Daniel R.↗
DOE OSTI2020

Synchronization-Based Guaranteed-Performance Formation Design for Swarm Systems

Guaranteed-performance formation control for swarm systems with the second-order dynamics is investigated based on the synchronization control strategy. Firstly, a new formation protocol is presented, where the weights of connected edges are adaptively regulated and the performance constraint is imposed. Then, on the basis of the Riccati inequality, sufficient conditions for synchronization-based guaranteed-performance formation are proposed, and an explicit expression of the guaranteed-performance cost is shown, where it is fully distributed to design gain matrices of the formation protocol in the sense that it is independent of global information of swarm systems. Moreover, the whole motion of a swarm system is determined, which is associated with initial states of all agents and formation control vectors. Finally, two numerical examples are shown to demonstrate theoretical conclusions, where the static whole motion and the dynamic whole motion are considered, respectively.

Dang, Hongtao↗
DOE OSTI2017

Statistical Analysis of Hubble /WFC3 Transit Spectroscopy of Extrasolar Planets

Transmission spectroscopy provides a window to study exoplanetary atmospheres, but that window is fogged by clouds and hazes. Clouds and haze introduce a degeneracy between the strength of gaseous absorption features and planetary physical parameters such as abundances. One way to break that degeneracy is via statistical studies. We collect all published HST /WFC3 transit spectra for 1.1–1.65 μ m water vapor absorption and perform a statistical study on potential correlations between the water absorption feature and planetary parameters. We fit the observed spectra with a template calculated for each planet using the Exo-transmit code. We express the magnitude of the water absorption in scale heights, thereby removing the known dependence on temperature, surface gravity, and mean molecular weight. We find that the absorption in scale heights has a positive baseline correlation with planetary equilibrium temperature; our hypothesis is that decreasing cloud condensation with increasing temperature is responsible for this baseline slope. However, the observed sample is also intrinsically degenerate in the sense that equilibrium temperature correlates with planetary mass. We compile the distribution of absorption in scale heights, and we find that this distribution is closer to log-normal than Gaussian. However, we also find that the distribution of equilibrium temperatures for the observed planets is similarly log-normal. This indicates that the absorption values are affected by observational bias, whereby observers have not yet targeted a sufficient sample of the hottest planets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Model-independent determination of the astrophysical S factor in laser-induced fusion plasmas

In this paper, we present a new and general method for measuring the astrophysical S factor of nuclear reactions in laser-induced plasmas and we apply it to 2 H(d,n) 3 He. The experiment was performed with the Texas Petawatt Laser, which delivered 150–270 fs pulses of energy ranging from 90 to 180 J to D 2 or CD 4 molecular clusters (where D denotes 2 H). After removing the background noise, we used the measured time-of-flight data of energetic deuterium ions to obtain their energy distribution. We derive the S factor using the measured energy distribution of the ions, the measured volume of the fusion plasma, and the measured fusion yields. This method is model independent in the sense that no assumption on the state of the system is required, but it requires an accurate measurement of the ion energy distribution, especially at high energies, and of the relevant fusion yields. In the 2 H(d,n) 3 He and 3 He(d,p) 4 He cases discussed here, it is very important to apply the background subtraction for the energetic ions and to measure the fusion yields with high precision. While the available data on both ion distribution and fusion yields allow us to determine with good precision the S factor in the d+d case (lower Gamow energies), for the d+ 3 He case the data are not precise enough to obtain the S factor using this method. Our results agree with other experiments within the experimental error, even though smaller values of the S factor were obtained. This might be due to the plasma environment differing from the beam target conditions in a conventional accelerator experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A new data-driven map predicts substantial undocumented peatland areas in Amazonia

Tropical peatlands are among the most carbon-dense terrestrial ecosystems yet recorded. Collectively, they comprise a large but highly uncertain reservoir of the global carbon cycle, with wide-ranging estimates of their global area (441 025–1700 000 km 2 ) and below-ground carbon storage (105–288 Pg C). Substantial gaps remain in our understanding of peatland distribution in some key regions, including most of tropical South America. Here we compile 2413 ground reference points in and around Amazonian peatlands and use them alongside a stack of remote sensing products in a random forest model to generate the first field-data-driven model of peatland distribution across the Amazon basin. Our model predicts a total Amazonian peatland extent of 251 015 km 2 (95th percentile confidence interval: 128 671–373 359), greater than that of the Congo basin, but around 30% smaller than a recent model-derived estimate of peatland area across Amazonia. The model performs relatively well against point observations but spatial gaps in the ground reference dataset mean that model uncertainty remains high, particularly in parts of Brazil and Bolivia. For example, we predict significant peatland areas in northern Peru with relatively high confidence, while peatland areas in the Rio Negro basin and adjacent south-western Orinoco basin which have previously been predicted to hold Campinarana or white sand forests, are predicted with greater uncertainty. Similarly, we predict large areas of peatlands in Bolivia, surprisingly given the strong climatic seasonality found over most of the country. Very little field data exists with which to quantitatively assess the accuracy of our map in these regions. Data gaps such as these should be a high priority for new field sampling. This new map can facilitate future research into the vulnerability of peatlands to climate change and anthropogenic impacts, which is likely to vary spatially across the Amazon basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2021

Mycorrhizal Distributions Impact Global Patterns of Carbon and Nutrient Cycling

Most tree species predominantly associate with a single type of mycorrhizal fungi, which can differentially affect plant nutrient acquisition and biogeochemical cycling. Uncertainties in mycorrhizal distributions are non-trivial, and current estimates disagree in up to 50% over 40% of the land area, including tropical forests. Remote sensing capabilities for mycorrhizal detection show promise for refining these estimates further. Here, we address for the first time the impact of mycorrhizal distributions on global carbon and nutrient cycling. Using the state-of-the-art carbon-nitrogen economics within the Community Land Model version 5, we found Net Primary Productivity (NPP) increased throughout the 21st century by 20%; however, as soil nitrogen has progressively become limiting, the costs to NPP for nitrogen acquisition—that is, to mycorrhizae—have increased at a faster rate by 60%. This suggests that nutrient acquisition will increasingly demand a higher portion of assimilated carbon to support the same productivity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Quantification of Steady-State Ion Transport through Single Conical Nanopores and a Nonuniform Distribution of Surface Charges

Electrostatic interactions of mobile charges in solution with the fixed surface charges are known to strongly affect stochastic sensing and electrochemical energy conversion processes at nanodevices or devices with nanostructured interfaces. The key parameter to describe this interaction, surface charge density (SCD), is not directly accessible at nanometer scale and often extrapolated from ensemble values. In this report, the steady-state current–voltage (i–V) curves measured using single conical glass nanopores in different electrolyte solutions are fitted by solving Poisson and Nernst–Planck equations through finite element approach. Both high and low conductivity state currents of the rectified i–V curve are quantitatively fitted in simulation at less than 5% error. The overestimation of low conductivity state current using existing models is overcome by the introduction of an exponential SCD distribution inside the conical nanopore. A maximum SCD value at the pore orifice is determined from the fitting of the high conductivity state current, while the distribution length of the exponential SCD gradient is determined by fitting the low conductivity state current. Quantitative fitting of the rectified i–V responses and the efficacy of the proposed model are further validated by the comparison of electrolytes with different types of cations (K + and Li + ). In conclusion, the gradient distribution of surface charges is proposed to be dependent on the local electric field distribution inside the conical nanopore.

77 NANOSCIENCE AND NANOTECHNOLOGY↗