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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 OSTI2020

Exploring the Use of DSCOVR/EPIC Satellite Observations to Monitor Vegetation Phenology

Vegetation phenology plays a pivotal role in regulating several ecological processes and has profound impacts on global carbon exchange. Large-scale vegetation phenology monitoring mostly relies on Low-Earth-Orbit satellite observations with low temporal resolutions, leaving gaps in data that are important for monitoring seasonal vegetation phenology. High temporal resolution satellite observations have the potential to fill this gap by frequently collecting observations on a global scale, making it easier to study change over time. This study explored the potential of using the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, which captures images of the entire sunlit face of the Earth at a temporal resolution of once every 1–2 h, to observe vegetation phenology cycles in North America. We assessed the strengths and shortcomings of EPIC-based phenology information in comparison with the Moderate-resolution Imaging Spectroradiometer (MODIS), Enhanced Thematic Mapper (ETM+) onboard Landsat 7, and PhenoCam ground-based observations across six different plant functional types. Our results indicated that EPIC could capture and characterize seasonal changes of vegetation across different plant functional types and is particularly consistent in the estimated growing season length. Our results also provided new insights into the complementary features and benefits of the four datasets, which is valuable for improving our understanding of the complex response of vegetation to global climate variability and other disturbances and the impact of phenology changes on ecosystem productivity and global carbon exchange.

Weber, Maridee A.↗
DOE OSTI2015

Tagged spectator deep-inelastic scattering as a tool to study neutron structure

The poster summarizes results from the FY14/15 JLab LDRD project "Physics potential of polarized light ions with EIC@JLab" regarding possible measurements of neutron structure functions (unpolarized and polarized) in deep-inelastic scattering with spectator nucleon tagging at a future Electron-Ion Collider. Also included are some results by Cosyn et al. regarding the theoretical description of the JLab 6 GeV BONuS data. Presented by W. Cosyn at 11th European Research Conference "Electromagneitc Interactions with Nucleons and Nuclei," Paphos, Cyprus, 1-7 November, 2015

Cosyn, Wim↗
DOE OSTI2021

Deep ocean metagenomes provide insight into the metabolic architecture of bathypelagic microbial communities

The deep sea, the largest ocean’s compartment, drives planetary-scale biogeochemical cycling. Yet, the functional exploration of its microbial communities lags far behind other environments. Here we analyze 58 metagenomes from tropical and subtropical deep oceans to generate the Malaspina Gene Database. Free-living or particle-attached lifestyles drive functional differences in bathypelagic prokaryotic communities, regardless of their biogeography. Ammonia and CO oxidation pathways are enriched in the free-living microbial communities and dissimilatory nitrate reduction to ammonium and H 2 oxidation pathways in the particle-attached, while the Calvin Benson-Bassham cycle is the most prevalent inorganic carbon fixation pathway in both size fractions. Reconstruction of the Malaspina Deep Metagenome-Assembled Genomes reveals unique non-cyanobacterial diazotrophic bacteria and chemolithoautotrophic prokaryotes. The widespread potential to grow both autotrophically and heterotrophically suggests that mixotrophy is an ecologically relevant trait in the deep ocean. These results expand our understanding of the functional microbial structure and metabolic capabilities of the largest Earth aquatic ecosystem.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Review of Amendment Delivery and Distribution Methods, and Relevance to Potential In Situ Source Area Treatment at the Hanford Site

The U.S. Department of Energy’s Hanford Site in southeastern Washington State is a complex of multiple facilities where historical release events in the Central Plateau area have resulted in subsurface contamination of the vadose zone, a perched-water zone, and underlying aquifer. Although some contaminants have already migrated through the vadose zone into the groundwater, contaminants remaining in the unsaturated zone are a potential long-term risk as a source for further groundwater contamination. Moreover, a perched-water zone located in the 200-DV-1 Operable Unit at Hanford creates further remediation difficulties. Remediation options are limited for contaminants located in the vadose and perched-water zones within the Central Plateau due to considerable depth, co-located contaminants, and complexities associated with physical and biogeochemical heterogeneities. Existing comprehensive reviews discuss potential remedial technologies relevant to Hanford Site conditions (e.g., deep vadose zone and perched water) and provide treatment technology recommendations. Many of the recommended in situ remediation technologies rely on introduction of amendments into the subsurface to achieve remedial goals. However, there are currently few review or guidance documents that provide a comprehensive look at mechanisms and considerations related to amendment delivery and distribution. This document summarizes amendment types, delivery techniques, subsurface access methods, and the applicability of delivery methods and amendments for specific subsurface target zones, including in the context of Hanford Central Plateau applications. Guidance on the appropriateness of a remedial technology for a specific site and contaminant is not included within this document. Rather, this document is intended to be used when considering remediation technologies and the associated amendments. An overview of amendment types (i.e., liquid, gas, and solids) and access/distribution methods used in subsurface remediation is provided, along with discussion of the maturity level (low, medium, or high), advantages, and limitations that relate to the potential effectiveness of each approach in the context of site-specific factors (subsurface geology, geochemistry, contaminant properties, etc.). There are many Hanford Site-specific factors that influence the suitability and appropriateness of amendment delivery strategies. Excluding amendment delivery approaches that are unsuitable for the Hanford context, each approach was assessed for applicability to the following target zones: unsaturated high permeability, unsaturated low permeability, perched water, saturated high permeability, and saturated low permeability zones. This compilation and discussion related to amendment delivery mechanisms provides a useful resource for evaluating remedial alternatives for source area contamination in the Hanford Central Plateau.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

DEEP NEAR-IR OBSERVATIONS OF THE GLOBULAR CLUSTER M4: HUNTING FOR BROWN DWARFS

We present an analysis of deep Hubble Space Telescope (HST)/Wide Field Camera 3 near-IR (NIR) imaging data of the globular cluster (GC) M4. The best-photometry NIR color–magnitude diagram (CMD) clearly shows the main sequence extending toward the expected end of the hydrogen-burning limit and going beyond this point toward fainter sources. The white dwarf (WD) sequence can be identified. As such, this is the deepest NIR CMD of a GC to date. Archival HST optical data were used for proper-motion cleaning of the CMD and for distinguishing the WDs from brown dwarf (BD) candidates. Detection limits in the NIR are around F110W ≈ 26.5 mag and F160W ≈ 27 mag, and in the optical around F775W ≈ 28 mag. Comparing our observed CMDs with theoretical models, we conclude that we have reached beyond the H-burning limit in our NIR CMD and are probably just above or around this limit in our optical–NIR CMDs. Thus, any faint NIR sources that have no optical counterpart are potential BD candidates, since the optical data are not deep enough to detect them. We visually inspected the positions of NIR sources that are fainter than the H-burning limit in F110W and for which the optical photometry did not return a counterpart. We found in total five sources for which we did not get an optical measurement. For four of these five sources, a faint optical counterpart could be visually identified, and an upper optical magnitude was estimated. Based on these upper optical magnitude limits, we conclude that one source is likely a WD, one source could be either a WD or BD candidate, and the remaining two sources agree with being BD candidates. No optical counterpart could be detected for just one source, which makes this source a good BD candidate. We conclude that we found in total four good BD candidates.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Computationally efficient CFD prediction of bubbly flow using physics-guided deep learning

To realize efficient computational fluid dynamics (CFD) prediction of two-phase flow, a multi-scale framework was proposed in this paper by applying a physics-guided data-driven approach. Instrumental to this framework, Feature Similarity Measurement (FSM) technique was developed for error estimation in two-phase flow simulation using coarse-mesh CFD, to achieve a comparable accuracy as fine-mesh simulations with fast-running feature. In this work, by defining physics-guided parameters and variable gradients as physical features, FSM has the capability to capture the underlying local patterns in the coarse-mesh CFD simulation. Massive low-fidelity data and respective high-fidelity data are used to explore the underlying information relevant to the main simulation errors and the effects of phenomenological scaling. By learning from previous simulation data, a surrogate model using deep feedforward neural network (DFNN) can be developed and trained to estimate the simulation error of coarse-mesh CFD. In a demonstration case of two-phase bubbly flow, the DFNN model well captured and corrected the unphysical “peaks” in the velocity and void fraction profiles near the wall in the coarse-mesh configuration, even for extrapolative predictions. The research documented supports the feasibility of the physics-guided deep learning methods for coarse mesh CFD simulations which has a potential for the efficient industrial design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Valuation of ecosystem services in alternative bioenergy landscape scenarios

Abstract Agricultural land in the Midwest is a source of food and fuel, as well as biodiversity. It is also a cause of excess nutrients that make their way to the Mississippi River and the Gulf of Mexico. To address unsustainable changes to biogeochemical cycles and ecosystem functions, a multidisciplinary approach involving social science, natural science, and engineering is often effective. Given the potential of second‐generation biofuels, and capitalizing on the deep‐rooted perennial bioenergy crops capable of thriving in poor soils, we demonstrated an integrated socio‐environmental analysis of the impacts of growing switchgrass within row‐crop landscapes in Illinois. In this study, we model land use scenarios that incorporate switchgrass as a biofuel crop in a Midwest corn‐belt watershed using the Soil Water Assessment Tool coupled with an economic analysis for the Vermilion Basin in Illinois. We estimated the values of ecosystem services under an alternative bioenergy landscape, including commodity and bioenergy crops, changes in biogeochemistry, and recreational services. The estimated annual values of nitrate and sediment reduction attributed to bioenergy crops range from $38 million to $97 million and $16,000 to $197,000, respectively. The annual value of carbon dioxide emission reduction ranges from $1.8 million to $6.1 million based on the initial crop rotation pattern. Estimated average annual values for wildlife viewing, water‐based recreation, and pheasant hunting are $1.24 million, $0.17 million, and $0.3 million, respectively. To our knowledge, this study represents the first effort to comprehensively quantify ecosystem services using a process‐based model, and estimate their value in an alternative bioenergy landscape. The information we generate could aid in understanding the potential for biomass production from marginal land and the total economic value of the landscape at various spatial scales. The framework is useful in fostering alternative bioenergy landscapes with synergies in a food, energy, and conservation nexus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry

Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library (MatGL), an open-source graph deep learning library for materials science and chemistry. Built on top of the popular Deep Graph Library (DGL) and Python Materials Genomics (Pymatgen) packages, MatGL is designed to be an extensible “batteries-included” library for developing advanced model architectures for materials property predictions and interatomic potentials. At present, MatGL has efficient implementations for both invariant and equivariant graph deep learning models, including the Materials 3-body Graph Network (M3GNet), MatErials Graph Network (MEGNet), Crystal Hamiltonian Graph Network (CHGNet), TensorNet and SO3Net architectures. MatGL also provides several pre-trained foundation potentials (FPs) with coverage of the entire periodic table, and property prediction models for out-of-box usage, benchmarking and fine-tuning. Finally, MatGL integrates with PyTorch Lightning to enable efficient model training.

chemistry↗
DOE OSTI2020

WRF Modelling of Deep Convection and Hail for Wind Power Applications

Deep convection and the related occurrence of hail, intense precipitation and wind gusts represent a hazard to a range of energy infrastructure including wind turbine blades. Wind turbine blade leading edge erosion (LEE) is caused by the impact of falling hydrometeors onto rotating wind turbine blades. It is a major source of wind turbine maintenance costs and energy losses from wind farms. In the United States Southern Great Plains (SGP), where there is widespread wind energy development, deep convection and hail events are common, increasing the potential for precipitation-driven LEE. A 25-day Weather Research and Forecasting (WRF) model simulation conducted at convection-permitting resolution and using a detailed microphysics scheme is carried out for the SGP to evaluate the effectiveness in modelling the wind and precipitation conditions relevant to LEE potential. WRF output for these properties is evaluated using radar observations of precipitation (including hail) and reflectivity, in situ wind speed measurements and wind power generation. This research demonstrates some skill for the primary drivers of LEE. Wind speeds, rainfall rates and precipitation totals show good agreement with observations. Here, the occurrence of precipitation during power producing wind speeds is also shown to exhibit fidelity. Hail events frequently occur during periods when wind turbines are rotating and are especially important to LEE in the SGP. The presence of hail is modelled with a mean proportion correct of 0.77 and an odds ratio 4.55. Further research is needed to demonstrate sufficient model performance to be actionable for the wind energy industry and there is evidence for positive model bias in cloud reflectivity.

17 WIND ENERGY↗
DOE OSTI2015

Abundant Atribacteria in deep marine sediment from the Adélie Basin, Antarctica

Bacteria belonging to the newly classified candidate phylum “Atribacteria” (formerly referred to as “OP9” and “JS1”) are common in anoxic methane-rich sediments. However, the metabolic functions and biogeochemical role of these microorganisms in the subsurface remains unrealized due to the lack of pure culture representatives. In this study of deep sediment from Antarctica’s Adélie Basin, collected during Expedition 318 of the Integrated Ocean Drilling Program (IODP), Atribacteria-related sequences of the 16S rRNA gene were abundant (up to 51% of the sequences) and steadily increased in relative abundance with depth throughout the methane-rich zones. To better understand the metabolic potential of Atribacteria within this environment, and to compare with phylogenetically distinct Atribacteria from non-deep-sea environments, individual cells were sorted for single cell genomics from sediment collected from 97.41 m below the seafloor from IODP Hole U1357C. As observed for non-marine Atribacteria, a partial single cell genome suggests a heterotrophic metabolism, with Atribacteria potentially producing fermentation products such as acetate, ethanol, and CO 2 . These products may in turn support methanogens within the sediment microbial community and explain the frequent occurrence of Atribacteria in anoxic methane-rich sediments. This first report of a single cell genome from deep sediment broadens the known diversity within the Atribacteria phylum and highlights the potential role of Atribacteria in carbon cycling in deep sediment.

Microbiology↗
DOE OSTI2021

Trapping interlayer excitons in van der Waals heterostructures by potential arrays

Transition metal dichalcogenide heterostructures can host interlayer excitons (IXs), which consist of electrons and holes spatially separated in different layers. IXs possess permanent dipoles and have proven to offer a wealth of novel physics. Here we develop a discrete, random-walk model which includes annihilation and repulsion interactions among IXs. Using this model, we simulate the trapping of IXs in traps of different depths, densities, and shapes. Our results show that dipole-dipole interactions play an important role in regulating IX trapping. The effects of dipole interactions can be mitigated with small, deep traps which are realizable with atomic defects and moire potentials.

2-dimensional systems↗
NASA NTRS2016

Beaconless Pointing for Deep-Space Optical Communication

Free space optical communication is of interest to NASA as a complement to existing radio frequency communication methods. The potential for an increase in science data return capability over current radio-frequency communications is the primary objective. Deep space optical communication requires laser beam pointing accuracy on the order of a few microradians. The laser beam pointing approach discussed here operates without the aid of a terrestrial uplink beacon. Precision pointing is obtained from an on-board star tracker in combination with inertial rate sensors and an outgoing beam reference vector. The beaconless optical pointing system presented in this work is the current approach for the Integrated Radio and Optical Communication (iROC) project.

free-space optical communication↗
DOE OSTI2019

Electrification Futures Study: Scenarios for Demand-Side Adoption in the United States

Electrification - the potential for increased electricity demand due to new services and the shift from any non-electric source of energy to electricity at the point of final consumption - is a major emerging trend in energy markets around the world. Select driving forces for this trend are a collection of newly-improved electric end-use technologies, engaged consumers and manufacturers, and a variety of economic and policy objectives in different jurisdictions. NREL and partners are conducting a multi-year study of electrification scenarios, which will explore research questions related to the potential key technologies for, planning requirements for, and impacts of deep electrification of the U.S. economy. NREL recently published a report that presents scenarios with various degrees of future electrification in all major end-use sectors of the U.S. energy system, and quantifies impacts on the amount and shape of national and regional electricity demand. In addition, ongoing analysis is exploring how the U.S. electricity system could need to transform to meet changes in demand from an electrified economy, the potential role of demand-side flexibility in supporting reliable operations of a clean electricity grid, and the potential costs, benefits, and impacts of mass electrification. This talk will serve to frame some of the overall boundaries of the session and report on electrification levels and impacts under a variety of scenarios.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS2015

Exploring Our Solar System with CubeSats and NanoSats

The Jet Propulsion Laboratory (JPL) is NASA's lead center for robotic exploration of our solar system. We are known for our large, flagship missions, such as Voyager, which gave humanity its first close look at Jupiter and Saturn; and the Mars Rovers, which have excited millions worldwide with their daring landing exploits. Less familiar to those outside NASA may be our role in developing the Kepler mission, which has discovered more than 2000 planets around other stars; or the recently launched Soil Moisture Active Passive (SMAP) mission, one of many JPL Earth Science missions. A recent JPL initiative has emphasized low cost missions that use rapidly evolving technology developed for CubeSats and NanoSat s to explore our solar system. Costs are significantly lower (by one or two orders of magnitude) than for conventional JPL missions, and development time is also significantly shorter. At present 21 such CubeSat flight projects are under way at the laboratory with various partners : some in flight, some in development, some in advanced formulation. Four are planned as deep space missions. To succeed in exploring deep space CubeSat/NanoSat missions have to address several challenges: the more severe radiation environment, communications and navigation at a distance, propulsion, and packaging of instruments that can return valuable science into a compact volume/mass envelope. Instrument technologies, including cameras, magnetometers, spectrometers, radiometers, and even radars are undergoing miniaturization to fit on these smaller platforms. Other key technologies are being matured for smallsats and NanoSats in deep space, including micro -electric propulsion, compact radio (and optical) communications, and onboard data reduction. This paper will describe missions that utilize these developments including the first two deep space CubeSats (INSPIRE), planned for launch in 2017; the first pair of CubeSats to be sent to another planet (MARCO), manifested with the InSight Mars lander launch in March of 2016; a helicopter "drone" on Mars to extend the reach of future rovers; plans for a Lunar Flashlight mission to shine a light on the permanently shadowed craters of the Moon's poles; a Near Earth Asteroid CubeSat missio n; and a CubeSat constellation to demonstrate time series measurements of storm systems on Earth. From these beginnings, the potential for CubeSats and NanoSats to add to our knowledge of the solar system could easily grow exponentially. Imagine if every deep space mission carried one or more CubeSats that could operate independently (even for a brief period) on arrival at their target body. At only incremental additional cost, such spacecraft could go closer, probe deeper, and provide science measurements that we would not risk with the host spacecraft. This paper will describe examples including a NanoSat to probe the composition of Venus' atmosphere, impactors and close flybys of Europa, lunar probes, and soft landers for the moons of Mars. Low cost access to deep space also offers the potential for independent CubeSat/NanoSat missions - allowing us to characterize the population of near Earth asteroids for example, deploy a constellation around Venus, or take closer looks at the asteroid belt.

Deep Space↗
DOE OSTI2016

SU-D-201-05: On the Automatic Recognition of Patient Safety Hazards in a Radiotherapy Setup Using a Novel 3D Camera System and a Deep Learning Framework

Purpose: Patient safety hazards such as a wrong patient/site getting treated can lead to catastrophic results. The purpose of this project is to automatically detect potential patient safety hazards during the radiotherapy setup and alert the therapist before the treatment is initiated. Methods: We employed a set of co-located and co-registered 3D cameras placed inside the treatment room. Each camera provided a point-cloud of fraxels (fragment pixels with 3D depth information). Each of the cameras were calibrated using a custom-built calibration target to provide 3D information with less than 2 mm error in the 500 mm neighborhood around the isocenter. To identify potential patient safety hazards, the treatment room components and the patient’s body needed to be identified and tracked in real-time. For feature recognition purposes, we used a graph-cut based feature recognition with principal component analysis (PCA) based feature-to-object correlation to segment the objects in real-time. Changes in the object’s position were tracked using the CamShift algorithm. The 3D object information was then stored for each classified object (e.g. gantry, couch). A deep learning framework was then used to analyze all the classified objects in both 2D and 3D and was then used to fine-tune a convolutional network for object recognition. The number of network layers were optimized to identify the tracked objects with >95% accuracy. Results: Our systematic analyses showed that, the system was effectively able to recognize wrong patient setups and wrong patient accessories. The combined usage of 2D camera information (color + depth) enabled a topology-preserving approach to verify patient safety hazards in an automatic manner and even in scenarios where the depth information is partially available. Conclusion: By utilizing the 3D cameras inside the treatment room and a deep learning based image classification, potential patient safety hazards can be effectively avoided.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Collisional excitation of C2H− by H2: New interaction potential and scattering calculations

Interstellar anions play an important role in astrochemistry as being tracers of the physical and chemical conditions in cold molecular clouds and circumstellar gas. The local thermodynamic equilibrium is generally not fulfilled in media where anions are detected and radiative and collisional data are required to model the observed lines. The C2H− anion has not yet been detected in the interstellar medium; however, collisional data could be used for non-LTE models that would help in identifying the most intense lines. For this purpose, we have computed the first 4D potential energy surface (PES) of the C2H−–H2 complex using an explicitly correlated coupled-cluster approach. The PES is characterized by a single deep minimum with a well-depth of 924.96 cm−1. From this interaction potential, we derived excitation cross sections and rate coefficients of C2H− induced by collisions with para- and ortho-H2. The results obtained for collisions with para-H2 are compared to previous calculations performed using a 2D-PES obtained from an average over H2 rotations.

Chemistry↗
DOE OSTI2015

Retrofitting a 1960s Split-Level, Cold-Climate Home

National programs such as Home Performance with ENERGY STAR® and numerous other utility air-sealing programs have made homeowners aware of the benefits of energy-efficiency retrofits. Yet these programs tend to focus only on the low-hanging fruit: they recommend air sealing the thermal envelope and ductwork where accessible, switching to efficient lighting and low-flow fixtures, and improving the efficiency of mechanical systems (though insufficient funds or lack of knowledge to implement these improvements commonly prevent the implementation of these higher cost upgrades). At the other end of the spectrum, various utilities across the country are encouraging deep energy retrofit programs. Although deep energy retrofits typically seek 50% energy savings, they are often quite costly and are most applicable to gut-rehab projects. A significant potential for lowering energy use in existing homes lies between the lowhanging fruit and deep energy retrofit approaches—retrofits that save approximately 30% in energy compared to the pre-retrofit conditions. The energy-efficiency measures need to be nonintrusive so the retrofit projects can be accomplished in occupied homes.

1960 split level↗
NASA NTRS1982

Modelling the core magnetic field of the earth

It is suggested that radial off-center dipoles located within the core of the earth be used instead of spherical harmonics of the magnetic potential in modeling the core magnetic field. The off-center dipoles, in addition to more realistically modeling the physical current systems within the core, are if located deep within the core more effective at removing long wavelength signals of either potential or field. Their disadvantage is that their positions and strengths are more difficult to compute, and such effects as upward and downward continuation are more difficult to manipulate. It is nevertheless agreed with Cox (1975) and Alldredge and Hurwitz (1964) that physical realism in models is more important than mathematical convenience. A radial dipole model is presented which agrees with observations of secular variation and excursions.

Harrison, C. G. A.↗