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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

La-doped ZnO nanoparticles: Simple solution-combusting preparation and applications in the wastewater treatment

Graphical abstract: La-doped ZnO nanoparticles have been successfully prepared by a simple solution combustion route and exhibit good adsorption for Cu and Pb ion from water systems. - Highlights: • La-doped ZnO nanoparticles were successfully prepared via a simple solution-combustion route. • The integration of La{sup 3+} ions into ZnO decreased the band-gap of ZnO nanoparticles. • La-doped ZnO nanoparticles could remove more Pb and Cu ions from water resources than undoped ZnO. - Abstract: La-doped ZnO nanoparticles have been successfully synthesized by a simple solution combustion method via employing a mixture of ethanol and ethyleneglycol (v/v = 60/40) as the solvent. Zinc acetate and oxygen gas in the atmosphere were used as zinc and oxygen sources, and La(NO{sub 3}){sub 3} as the doping reagent. The as-obtained product was characterized by means of powder X-ray diffraction, scanning electron microscopy, transmission electron microscopy, energy dispersive X-ray spectrometry and X-ray photoelectron spectroscopy. Experiments showed that La-doped ZnO nanoparticles exhibited the higher capacities for the removal of Pb{sup 2+} and Cu{sup 2+} ions in water resource than undoped ZnO nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Comparison of numerical weather prediction based deterministic and probabilistic wind resource assessment methods

Numerical weather prediction (NWP) models have been widely used for wind resource assessment. Model runs with higher spatial resolution are generally more accurate, yet extremely computational expensive. An alternative approach is to use data generated by a low resolution NWP model, in conjunction with statistical methods. In order to analyze the accuracy and computational efficiency of different types of NWP-based wind resource assessment methods, this paper performs a comparison of three deterministic and probabilistic NWP-based wind resource assessment methodologies: (i) a coarse resolution (0.5 degrees x 0.67 degrees) global reanalysis data set, the Modern-Era Retrospective Analysis for Research and Applications (MERRA); (ii) an analog ensemble methodology based on the MERRA, which provides both deterministic and probabilistic predictions; and (iii) a fine resolution (2-km) NWP data set, the Wind Integration National Dataset (WIND) Toolkit, based on the Weather Research and Forecasting model. Results show that: (i) as expected, the analog ensemble and WIND Toolkit perform significantly better than MERRA confirming their ability to downscale coarse estimates; (ii) the analog ensemble provides the best estimate of the multi-year wind distribution at seven of the nine sites, while the WIND Toolkit is the best at one site; (iii) the WIND Toolkit is more accurate in estimating the distribution of hourly wind speed differences, which characterizes the wind variability, at five of the available sites, with the analog ensemble being best at the remaining four locations; and (iv) the analog ensemble computational cost is negligible, whereas the WIND Toolkit requires large computational resources. Future efforts could focus on the combination of the analog ensemble with intermediate resolution (e.g., 10-15 km) NWP estimates, to considerably reduce the computational burden, while providing accurate deterministic estimates and reliable probabilistic assessments.

17 WIND ENERGY↗
DOE OSTI2016

Final Report

This report summarizes our research activities. In the award period, we have made significant progress on the first aim, with new discoveries reported in one published paper (1) and in one submitted manuscript (2) currently under review. The published manuscript reports on our discovery of plant ribokinase and the metabolic pathway in which it functions; the submitted manuscript is identification and characterization of the plant fructokinase family of enzymes from expression studies, sequence comparisons, subcellular localizations and enzymatic activities of recombinant proteins. Our study of loss-of-function mutants in the fructokinase family members (2) revealed that there were no phenotypic differences observed for the five genes analyzed, so we have adopted the Crispr/Cas9 system to isolate mutants in the two genes for which there are no currently available insertion mutants, and we are generating higher order mutants (double, triples, etc) to discern the relative roles and significance for each fructokinase. These mutants will be an important resource to understand regulation of carbohydrate movement and catabolism in plants. As studies from others indicate, alteration of fructokinases results in changes in cell walls and vasculatures, which have importance relative to biofuel yield and quality. In the second aim, we have characterized the protein-protein interactions for the pkfB proteins FLN1 and FLN2 that are localized to chloroplast transcriptional complexes and have proposed a new model for how chloroplast transcription is regulated. This work has been submitted for publication, been revised and will be re-submitted in December 2016

09 BIOMASS FUELS↗
DOE OSTI2011

Updated U.S. Geothermal Supply Characterization and Representation for Market Penetration Model Input

The U.S. Department of Energy (DOE) Geothermal Technologies Program (GTP) tasked the National Renewable Energy Laboratory (NREL) with conducting the annual geothermal supply curve update. This report documents the approach taken to identify geothermal resources, determine the electrical producing potential of these resources, and estimate the levelized cost of electricity (LCOE), capital costs, and operating and maintenance costs from these geothermal resources at present and future timeframes under various GTP funding levels. Finally, this report discusses the resulting supply curve representation and how improvements can be made to future supply curve updates.

14 SOLAR ENERGY↗
DOE OSTI2025

Nanomaterial-Engineered Surfaces for Decontamination of Water Resources

Aggregation-dependent shifts in plasmon frequency (colorimetric sensor); • Local refractive index-dependent shifts in plasmon frequency; • Inelastic (surface-enhanced Raman) light scattering; • Elastic (Rayleigh) light scattering CONCLUSIONS Generate unique classes of nanoscale materials for environmental stewardship applications o Characterization of nanomaterials provides understanding of structural properties for sorption of contaminants o Surface charge influences interaction between nanomaterial and contaminant o Surface charge can be modified to allow for more contaminant sorption • Demonstrate innovative nanomaterial science and technology solutions that meet our environmental stewardship needs: • Detect contaminants • Sequester contaminants

Murph, Simona E. [Savannah River National Laborato↗
DOE OSTI2026

Uncertain quantum computing futures and potential energy and physical resource impacts at scale

Considerable attention has recently focused on the vast energy and water demands of supercomputing, namely large-scale data centers that underpin artificial intelligence (AI), one of the great disruptors of contemporary society. Looking ahead some years from now, quantum computing is poised to disrupt established computing paradigms once again. Scientists and engineers are now working intensely to bring this century-old dream of physicists to fruition. Yet, as quantum computers begin to be integrated with classical supercomputing architectures, the implications for energy and physical resource use also need to be understood, especially how they compare to today’s AI data centers. These impacts have not yet been quantified by the research community – a notable gap in the literature, even if commercial-scale deployment of Quantum-Accelerated Computing Infrastructure (QuACI) is not expected for a few more years. This study is the first to conduct such an assessment. Using publicly available information from academic sources and private industry, we characterize multiple configurations of superconducting qubit-based, fault-tolerant quantum computers (FTQC) that could plausibly be deployed at scale in the 2030s and into the 2040s. By parameterizing these FTQC systems at a process level, we conduct a prospective scenario analysis to quantify their energy and physical resource needs. While these estimates are uncertain, given the current state of quantum technologies and their unknown future trajectories, important insights can already be drawn. One key finding is that while the electricity needs for a fleet of FTQCs are within the bounds of previous modeling studies that have explored high electricity demand futures, the needs for certain physical resources, namely water and helium-3, could pose bottlenecks to QuACI scale-up.

Computing↗
DOE OSTI2013

Transcriptome Analysis in Sheepgrass (Leymus chinensis). A Dominant Perennial Grass of the Eurasian Steppe

BACKGROUND: Sheepgrass [Leymus chinensis (Trin.) Tzvel.] is an important perennial forage grass across the Eurasian Steppe and is known for its adaptability to various environmental conditions. However, insufficient data resources in public databases for sheepgrass limited our understanding of the mechanism of environmental adaptations, gene discovery and molecular marker development. RESULTS: The transcriptome of sheepgrass was sequenced using Roche 454 pyrosequencing technology. We assembled 952,328 high-quality reads into 87,214 unigenes, including 32,416 contigs and 54,798 singletons. There were 15,450 contigs over 500 bp in length. BLAST searches of our database against Swiss-Prot and NCBI non-redundant protein sequences (nr) databases resulted in the annotation of 54,584 (62.6%) of the unigenes. Gene Ontology (GO) analysis assigned 89,129 GO term annotations for 17,463 unigenes. We identified 11,675 core Poaceae-specific and 12,811 putative sheepgrass-specific unigenes by BLAST searches against all plant genome and transcriptome databases. A total of 2,979 specific freezing-responsive unigenes were found from this RNAseq dataset. We identified 3,818 EST-SSRs in 3,597 unigenes, and some SSRs contained unigenes that were also candidates for freezing-response genes. Characterizations of nucleotide repeats and dominant motifs of SSRs in sheepgrass were also performed. Similarity and phylogenetic analysis indicated that sheepgrass is closely related to barley and wheat. CONCLUSIONS: This research has greatly enriched sheepgrass transcriptome resources. The identified stress-related genes will help us to decipher the genetic basis of the environmental and ecological adaptations of this species and will be used to improve wheat and barley crops through hybridization or genetic transformation. The EST-SSRs reported here will be a valuable resource for future gene-phenotype studies and for the molecular breeding of sheepgrass and other Poaceae species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Confirmation and Quantification of Gas Flow into Capsules

Inertial confinement fusion experiments require a fuel filled target. At the National Ignition Facility (NIF), these targets are filled through a capsule fill tube assembly (CFTA). While fabricating these assemblies, it is possible to plug the fill tube with glue, which would render the CFTA and eventual target unusable. Historically, this plugging was first detectable in a finished target after considerable resources had been expended. Herein, this paper presents a method for not only detecting a plug in the fill tube before the CFTA is assembled into a target, but also characterizing gas flow through the fill tube, which can help NIF operations prepare to expend each target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

On the Stability of Power Transmission Systems Under Persistent Inverter Attacks: A Bi-Linear Matrix Approach

We investigate the stability and robustness properties of a power transmission system under persistent deceiving attacks on inverter-interfaced energy resources. The attacks can corrupt the damping coefficients in the inverters' controllers and measurements of the frequency at the points of coupling. Leveraging tools from hybrid dynamical systems theory, we characterize a broad family of persistent (and not necessarily periodic) attacks acting on the inverters, under which the stability properties of the transmission system can be shown to not be compromised. To address potentially conservative conditions identified through conventional bounding techniques, sufficient conditions on the average activation time of the attacks are identified via Lyapunov theory, as well as the formulation and solution of a class of bilinear matrix inequalities (BMI). The results are obtained for constant and slowly time-varying loads via input-to-state stability (ISS) tools. Numerical simulations on the IEEE 39-bus test system are also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Optimal test selection for prediction uncertainty reduction

Economic factors and experimental limitations often lead to sparse and/or imprecise data used for the calibration and validation of computational models. This paper addresses resource allocation for calibration and validation experiments, in order to maximize their effectiveness within given resource constraints. When observation data are used for model calibration, the quality of the inferred parameter descriptions is directly affected by the quality and quantity of the data. This paper characterizes parameter uncertainty within a probabilistic framework, which enables the uncertainty to be systematically reduced with additional data. The validation assessment is also uncertain in the presence of sparse and imprecise data; therefore, this paper proposes an approach for quantifying the resulting validation uncertainty. Since calibration and validation uncertainty affect the prediction of interest, the proposed framework explores the decision of cost versus importance of data in terms of the impact on the prediction uncertainty. Often, calibration and validation tests may be performed for different input scenarios, and this paper shows how the calibration and validation results from different conditions may be integrated into the prediction. Then, a constrained discrete optimization formulation that selects the number of tests of each type (calibration or validation at given input conditions) is proposed. Furthermore, the proposed test selection methodology is demonstrated on a microelectromechanical system (MEMS) example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Utah FORGE: X-Ray Diffraction Data

This dataset contains X-ray diffraction (XRD) data taken from wells and outcrops as part of the DOE GTO supported Utah FORGE project located near Roosevelt Hot Springs. It contains an Excel spreadsheet with the XRD data, a text file with sample site names, types, and locations in UTM, Zone 12, NAD83 coordinates, and a GIS shapefile of the sample locations with attributes.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Utah FORGE: GIS Well Temperature Data

This is a GIS point feature shapefile representing wells, and their temperatures, that are located in the general Utah FORGE area near Milford, Utah. There are also fields that represent interpolated temperature values at depths of 200 m, 1000 m, 2000 m, 3000 m, and 4000 m. in degrees Fahrenheit. The temperature values at specific depths as mentioned above were derived as follows. In cases where the well reached a given depth (200 m and 1, 2, 3, or 4 km), the temperature is the measured temperature. For the shallower wells (and at deeper depths in the wells reaching one or more of the target depths), temperatures were extrapolated from the temperature-depth profiles that appeared to have stable (re-equilibrated after drilling) and linear profiles within the conductive regime (i.e. below the water table or other convective influences such as shallow hydrothermal outflow from the Roosevelt Hydrothermal System). Measured temperatures/gradients from deeper wells (when available and reasonably close to a given well) were used to help constrain the extrapolation to greater depths. Most of the field names in the attribute table are intuitive, however HF = heat flow, intercept = the temperature at the surface (x-axis of the temperature-depth plots) based on the linear segment of the plot that was used to extrapolate the temperature profiles to greater depths, and depth_m is the total well depth. This information is also present in the shapefile metadata.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Velocity and Turbulence Measurements at Three Locations in the Salish Sea, WA, 2017

This submission contains raw and processed datasets of water velocity and turbulence measurements from 3-day deployments of Deepwater Buoyancy StableMoor buoys carrying acoustic Doppler instrumentation at locations in Rosario Strait, Bellingham Channel, and Tacoma Narrows, WA in 2017. Two StableMoor buoy configurations were used at these sites. The StableMoor500 carried a nose-mounted acoustic doppler velocimeter (ADV) and a down-looking acoustic doppler current profiler (ADCP), and the StableMoor400 carried dual wing-mounted ADVs located on either side of the nose and a down-looking ADCP. Each StableMoor was designed to fly at an altitude of 10 m above the seafloor. The StableMoor500 was deployed in Bellingham Channel at 48.5601 N, 122.7501 W in 86 m of water from July 24, 2017 - July 27, 2017. The down-looking ADCP malfunctioned, and therefore there is no ADCP data at this site. The StableMoor400 was deployed in Rosario Strait mooring at 48.5800 N, 122.6597 W in 52 m of water from July 24, 2017 - July 27, 2017. Both buoys were deployed in Tacoma Narrows at 47.2766 N, 122.5466 W and 47.2769 N, 122.5471 W in 36 m of water from Nov 14, 2017 - Nov 17, 2017. Nortek Vector ADV measurements were recorded continuously at 16 Hz. Data was motion-corrected using the internal measurement unit (IMU) and external ADCP bottom-track data, bin-averaged into 10 minute bins, and then converted to the Principal (streamwise, cross-stream, vertical) coordinate system. Parameters include water velocity, turbulence intensity, turbulent kinetic energy (TKE) components, Reynolds shear stress components, TKE dissipation and production. Teledyne RDI Workhorse 1200 kHz ADCP measurements were recorded continuously at 2 Hz with bottom-track enabled. Water velocity was averaged into 10 minute bins and converted into the Principal coordinate system. One ADV with the highest quality motion-corrected was fully processed from each deployment site: the nose-mounted ADV at Bellingham Channel, the starboard-wing mounted ADV at Rosario Strait, and the port-wing mounted ADV at Tacoma Narrows. Raw data stored in this submission can be read using DOLfYN v1.3.1, available through the MHKiT python package, and was processed using Tsdat v0.7.5. Processed data are stored in netCDF4 format and can be easily viewed using the Linux "ncdump" command or read through the Xarray python package.

16 TIDAL AND WAVE POWER↗
DOE OSTI2014

The perfect heist :

Of the many facets of the criminal world, few have captured society s fascination as has that of high stakes robbery. The combination of meticulousness, cunning, and audacity required to execute a real-life Ocean s Eleven may be uncommon among criminals, but fortunately it is common enough to extract a wealth of lessons for the protection of high-value assets. To assist in informing the analyses and decisions of security professionals, this paper surveys 23 sophisticated and high-value heists that have occurred or been attempted around the world, particularly over the past three decades. The results, compiled in a Heist Methods and Characteristics Database, have been analyzed qualitatively and quantitatively, with the goals of both identifying common characteristics and characterizing the range and diversity of criminal methods used. The analysis is focused in six areas: (1) Defeated Security Measures and Devices, (2) Deception Methods, (3) Timing, (4) Weapons, (5) Resources, and (6) Insiders.

Lafleur, Jarret Marshall↗
DOE OSTI2023

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

Alexeev, Yuri↗