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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Piloted Well Clear Performance Evaluation of Detect and Avoid Systems with Suggestive Guidance

Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions (RTCA, 2013). Those requirements will apply to the new detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the United States (U.S) National Airspace System (NAS) and will be determined according to their contribution to the overall safety case. That safety case requires demonstration that DAA-equipped UAS collectively operating in the NAS meet an airspace safety threshold (AST). Several key gaps must be closed in order to link equipment requirements to an airspace safety case. Foremost among these is calculation of the systems risk ratio, the degree to which a particular system mitigates violation of an aircraft separation standard (FAA, 2013). The risk ratio of a DAA system, in combination with risk ratios of other collision mitigation mechanisms, will determine the overall safety of the airspace measured in terms of the number of collisions per flight hour. It is not known what the effectiveness is of a pilot-in-the-loop DAA system or even what parameters of the DAA system most improve the pilots ability to maintain separation. The relationship between the DAA system design and the overall effectiveness of the DAA system that includes the pilot, expressed as a risk ratio, must be determined before DAA operational and performance requirements can be finalized. Much research has been devoted to integrating UAS into non-segregated airspace (Dalamagkidis, 2009, Ostwald, 2007, Gillian, 2012, Hesselink, 2011, Santiago, 2015, Rorie 2015 and 2016). Several traffic displays intended for use as part of a DAA system have gone through human-in-the-loop simulation and flight-testing. Most of these evaluations were part of development programs to produce a deployable system, so it is unclear how to generalize particular aspects of those designs to general requirements for future traffic displays (Calhoun, 2014). Other displays have undergone testing to collect data that may generalize to new displays, but have not been evaluated in the context of the development of an overall safety case for UAS equipped with DAA systems in the NAS (Bell, 2012). Other research efforts focus on DAA surveillance performance and separation standards. Together with this work, they are expected to facilitate validation of the airspace safety case (Park, 2014 and Johnson, 2015). The contribution of the present work is to quantify the effectiveness of the pilot-automation system to remain well clear as a function of display features and surveillance sensor error. This quantification will help enable selection of a minimum set of DAA design features that meets the AST, a set that may not be unique for all UAS platforms. A second objective is to collect and analyze pilot performance parameters that will improve the modeling of overall DAA system performance in non-human-in-the-loop simulations. Simulating the DAA-equipped UAS in such batch experiments will allow investigation of a much larger number of encounters than is possible in human simulations. This capability is necessary to demonstrate that a particular set of DAA requirements meets the AST under all foreseeable operational conditions.

detect and avoid↗
DOE OSTI2022

A reverse-selective ion exchange membrane for the selective transport of phosphates via an outer-sphere complexation–diffusion pathway

Specific-ion selectivity is a highly desirable feature for the next generation of membranes. However, existing membranes rely on differences in charge, size and hydration energy, which limits their ability to target individual ion species. Here we demonstrate a nanocomposite ion-exchange membrane material that enables a reverse-selective transport mechanism that can selectively pass a single ion species. Here we demonstrate this transport mechanism with phosphate ions selectively transporting across negatively charged cation exchange membranes. Selective transport is enabled by the in situ growth of hydrous manganese oxide nanoparticles throughout a cation exchange membrane that provide a diffusion pathway via phosphate-specific, reversible outer-sphere interactions. On incorporating the hydrous manganese oxide nanoparticles, the membrane’s phosphate flux increased by a factor of 27 over an unmodified cation exchange membrane, and the selectivity of phosphorous over sulfate, nitrate and chloride reaches 47,100 and 20, respectively. By pairing ion-specific outer-sphere interactions between the target ions and appropriate nanoparticles, these nanocomposite ion-exchange materials can, in principle, achieve selective transport for a range of ions.

42 ENGINEERING↗
DOE OSTI2021

Simulation of Electron-Proton Scattering Events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN)

We apply generative adversarial network (GAN) technology to build an event generator that simulates particle production in electron-proton scattering that is free of theoretical assumptions about underlying particle dynamics. The difficulty of efficiently training a GAN event simulator lies in learning the complicated patterns of the distributions of the particles physical properties. We develop a GAN that selects a set of transformed features from particle momenta that can be generated easily by the generator, and uses these to produce a set of augmented features that improve the sensitivity of the discriminator. The new Feature-Augmented and Transformed GAN (FAT-GAN) is able to faithfully reproduce the distribution of final state electron momenta in inclusive electron scattering, without the need for input derived from domain-based theoretical assumptions. The developed technology can play a significant role in boosting the science of existing and future accelerator facilities, such as the Electron-Ion Collider.

Alanazi, Yasir↗
NASA NTRS1993

Electron microscope observations of impact crater debris amongst contaminating particulates on materials surfaces exposed in space in low-Earth orbit

Debris particles extracted from a small sampling region on the leading edge of the Long Duration Exposure Facility (LDEF) spacecraft have been examined by analytical transmission electron microscopy and the elemental frequency observed by energy-dispersive X-ray spectrometry and compared with upper atmosphere (Earth) particle elemental frequency and the average elemental compositions of interplanetary dust particles. A much broader elemental distribution was observed for the exposed spacecraft surface debris milieu. Numerous metal microfragment analyses, particularly aluminum and stainless steel, were compared with scanning electron microscope observations-of impact crater features, and the corresponding elemental spectra on selected LDEF aluminium tray clamps and stainless steel bolts. The compositions and melt features for these impact craters and ejecta have been shown to be consistent with microcrystalline debris fragments in the case of aluminum, and these observations suggest an ever changing debris milieu on exposed surfaces for space craft and space system materials.

Murr, L. E.↗
NASA NTRS1980

SPS solid state antenna power combiner

A concept for a solar power satellite antenna power combiner which utilizes solid state dc-rf converters is described. To avoid the power combining losses associated with circuit hybrids it is proposed that the power from multiple solid state amplifiers be combined by direct coupling of each amplifier's output to the radiating antenna structure. The selected power-combining antenna consists of a printed (metalized) microstrip circuit on a ceramic type dielectric substrate which is backed by a shallow lightweight aluminum cavity which sums the power of four microwave sources. The antenna behaves like two one-half wavelength slot-line antennas coupled together via their common cavity structure. A significant feature of the antenna configuration selected is that the radiated energy is summed to yield a single radiated output phase which represents the average insertion phase of the four power amplifiers. This energy may be sampled and, by comparison with the input signal, one can phase error correct to maintain the insertion phase of all solid state power combining modules at exactly the same value. This insures that the insertion phase of each SPS power combining antenna module is identical. An experiment verification program is described.

Fitzsimmons, G. W.↗
DOE OSTI2024

Identifying critical features of iron phosphate particle for lithium preference

One-dimensional (1D) olivine iron phosphate (FePO 4 ) is widely proposed for electrochemical lithium (Li) extraction from dilute water sources, however, significant variations in Li selectivity were observed for particles with different physical attributes. Understanding how particle features influence Li and sodium (Na) co-intercalation is crucial for system design and enhancing Li selectivity. Here, we investigate a series of FePO 4 particles with various features and revealed the importance of harnessing kinetic and chemo-mechanical barrier difference between lithiation and sodiation to promote selectivity. The thermodynamic preference of FePO 4 provides baseline of selectivity while the particle features are critical to induce different kinetic pathways and barriers, resulting in different Li to Na selectivity from 6.2 × 10 2 to 2.3 × 10 4 . Importantly, we categorize the FePO 4 particles into two groups based on their distinctly paired phase evolutions upon lithiation and sodiation, and generate quantitative correlation maps among Li preference, morphological features, and electrochemical properties. By selecting FePO 4 particles with specific features, we demonstrate fast (636 mA/g) Li extraction from a high Li source (1: 100 Li to Na) with (96.6 ± 0.2)% purity, and high selectivity (2.3 × 10 4 ) from a low Li source (1: 1000 Li to Na) with (95.8 ± 0.3)% purity in a single step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2009

First Spectroscopic Identification of Massive Young Stellar Objects in the Galactic Center

We report the detection of several molecular gas-phase and ice absorption features in three photometrically-selected young stellar object (YSO) candidates in the central 280 pc of the Milky Way. Our spectra, obtained with the Infrared Spectrograph (IRS) onboard the Spitzer Space Telescope, reveal gas-phase absorption from CO2 (15.0 microns), C2H2 (13.7 microns) and HCN (14.0 microns). We attribute this absorption to warm, dense gas in massive YSOs. We also detect strong and broad 15 microns CO2 ice absorption features, with a remarkable double-peaked structure. The prominent long-wavelength peak is due to CH3OH-rich ice grains, and is similar to those found in other known massive YSOs. Our IRS observa.tions demonstra.te the youth of these objects, and provide the first spectroscopic identification of massive YSOs in the Galactic Center.

An, Deokkeun↗
DOE OSTI2023

How plane are plane shock waves in solids

The notion of plane shock waves is a macroscopic, very fruitful idealization of near discontinuous disturbance propagating at supersonic speed. Such a picture is comparable to the picture of shorelines seen from a very high altitude. When viewed at the grain scale where the structure of solids is inherently heterogeneous and stochastic, features of shock waves are non-laminar and field variables, such as particle velocity and pressure, fluctuate. This paper reviews select aspects of such fluctuating nonequilibrium features of plane shock waves in solids with focus on grain scale phenomena and raises the need for a paradigm change to achieve a deeper understanding of plane shock waves in solids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Improving materials property predictions for graph neural networks with minimal feature engineering *

Graph neural networks (GNNs) have been employed in materials research to predict physical and functional properties, and have achieved superior performance in several application domains over prior machine learning approaches. Recent studies incorporate features of increasing complexity such as Gaussian radial functions, plane wave functions, and angular terms to augment the neural network models, with the expectation that these features are critical for achieving a high performance. Here, we propose a GNN that adopts edge convolution where hidden edge features evolve during training and extensive attention mechanisms, and operates on simple graphs with atoms as nodes and distances between them as edges. As a result, the same model can be used for very different tasks as no other domain-specific features are used. With a model that uses no feature engineering, we achieve performance comparable with state-of-the-art models with elaborate features for formation energy and band gap prediction with standard benchmarks; we achieve even better performance when the dataset size increases. Although some domain-specific datasets still require hand-crafted features to achieve state-of-the-art results, our selected architecture choices greatly reduce the need for elaborate feature engineering and still maintain predictive power in comparison.

42 ENGINEERING↗
NASA NTRS1987

USSR Space Life Sciences Digest, issue 11

This is the eleventh issue of NASA's USSR Space Life Sciences Digest. It contains abstracts of 54 papers recently published in Russian language periodicals and bound collections and of four new Soviet monographs. Selected abstracts are illustrated. Additional features include the translation of a paper presented in Russian to the United Nations, a review of a book on space ecology, and report of a conference on evaluating human functional capacities and predicting health. Current Soviet Life Sciences titles available in English are cited. The materials included in this issue have been identified as relevant to 30 areas of aerospace medicine and space biology. These areas are: adaptation, aviation physiology, biological rhythms, biospherics, body fluids, botany, cardiovascular and respiratory systems, cosmonaut training, developmental biology, endocrinology, enzymology, equipment and instrumentation, gastrointestinal systems, group dynamics, genetics, hematology, human performance, immunology, life support systems, mathematical modeling, metabolism, microbiology, musculoskeletal system, neurophysiology, nutrition, operational medicine, perception, personnel selection, psychology, and radiobiology.

Hooke, Lydia Razran↗
NASA NTRS2017

Lessons Learned from OSIRIS-Rex Autonomous Navigation Using Natural Feature Tracking

The Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (Osiris-REx) spacecraft is scheduled to launch in September, 2016 to embark on an asteroid sample return mission. It is expected to rendezvous with the asteroid, Bennu, navigate to the surface, collect a sample (July 20), and return the sample to Earth (September 23). The original mission design called for using one of two Flash Lidar units to provide autonomous navigation to the surface. Following Preliminary design and initial development of the Lidars, reliability issues with the hardware and test program prompted the project to begin development of an alternative navigation technique to be used as a backup to the Lidar. At the critical design review, Natural Feature Tracking (NFT) was added to the mission. NFT is an onboard optical navigation system that compares observed images to a set of asteroid terrain models which are rendered in real-time from a catalog stored in memory on the flight computer. Onboard knowledge of the spacecraft state is then updated by a Kalman filter using the measured residuals between the rendered reference images and the actual observed images. The asteroid terrain models used by NFT are built from a shape model generated from observations collected during earlier phases of the mission and include both terrain shape and albedo information about the asteroid surface. As a result, the success of NFT is highly dependent on selecting a set of topographic features that can be both identified during descent as well as reliably rendered using the shape model data available. During development, the OSIRIS-REx team faced significant challenges in developing a process conducive to robust operation. This was especially true for terrain models to be used as the spacecraft gets close to the asteroid and higher fidelity models are required for reliable image correlation. This paper will present some of the challenges and lessons learned from the development of the NFT system which includes not just the flight hardware and software but the development of the terrain models used to generate the onboard rendered images.

Navigation↗
DOE OSTI2020

A Versatile Remediation Module for Remote Repair of Spent Nuclear Fuel and High-Level Waste Storage Containers

Oak Ridge National Laboratory (ORNL) successfully demonstrated the Versatile Remediation Module (VRM), a prototype module designed and built by ORNL for on-site remote repair of welded stainless steel storage containers for spent nuclear fuel and high-level radioactive waste. This paper describes the VRM prototype and its design features and components to support continued long-term storage or off-site transportation of spent nuclear fuel and high-level radioactive waste currently stored in storage containers. A remote (100 ft away from the simulated radiative environment) demonstration of the VRM was successfully performed on a full-scale mock-up welded stainless steel canister. The VRM is designed with features to accommodate remediation techniques beyond those currently selected and described in this paper. Therefore, many of the VRM’s features may benefit other remote nuclear or nonnuclear applications. The VRM is envisioned to serve as a development center to facilitate and enhance further development of new remediation technologies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Versatile Remediation Module Final Operational Testing Results

Oak Ridge National Laboratory (ORNL) successfully demonstrated the Versatile Remediation Module (VRM), a prototype module designed and built by ORNL for performing the on-site remote repair of welded stainless-steel storage containers for spent nuclear fuel and high-level radioactive waste. This report describes the VRM prototype and its design features, components, qualification tests, operational procedures, and demonstration results to support continued long-term storage or off-site transportation of spent nuclear fuel and high-level radioactive waste currently stored in storage containers. A remote (i.e., 100 ft away from the simulated radiative environment) demonstration of the VRM was successfully performed on a full-scale mock-up welded stainless-steel canister. The VRM is designed with features to accommodate remediation techniques beyond those currently selected and described in this report. Therefore, many of the VRM’s features could benefit other remote nuclear or nonnuclear applications. The VRM is envisioned to serve as a development center to facilitate and enhance the further development of new remediation technologies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Preventing Loss of Selectivity during the Oxidative Dehydrogenation of Propane over Supported Vanadium Catalysts

Supported vanadium materials are promising catalysts for the oxidative dehydrogenation of propane to propylene (ODHP), but a lack of mechanistic understanding limits the rational design of catalysts with improved propylene selectivity. Adding Ta to V/SiO 2 increases the propylene selectivity, as well as the activity, leading to superior performance compared to state-of-the-art boron-based systems. In this contribution, we utilize this surprising promotional effect of Ta to elucidate key elements of the mechanistic cycle. Through a combination of characterization techniques, computational modeling, and kinetic experiments, we show that the catalytic cycle over V/SiO 2 likely involves the formation of an isopropyl alcohol intermediate, the fate of which is in kinetic competition between subsequent dehydration to propylene or further oxidation. Furthermore, we show that the relatively facile propylene overoxidation observed for these materials occurs via the epoxidation of propylene by a proposed peroxovanadium intermediate, rather than the abstraction of propylene’s allylic C–H bond as previously assumed. Using these key mechanistic features, we rationalize the enhanced selectivity and activity of Ta promotion. In conclusion, our mechanistic framework offers avenues for future catalyst development to improve supported vanadium materials for ODHP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Combustor and Vane Features and Components Tested in a Gas Turbine Environment

The use of ceramic matrix composites (CMCs) as combustor liners and turbine vanes provides the potential of improving next-generation turbine engine performance, through lower emissions and higher cycle efficiency, relative to today s use of superalloy hot-section components. For example, the introduction of film-cooling air in metal combustor liners has led to higher levels of nitrogen oxide (NOx) emissions from the combustion process. An environmental barrier coated (EBC) siliconcarbide- fiber-reinforced silicon carbide matrix (SiC/SiC) composite is a new material system that can operate at higher temperatures, significantly reducing the film-cooling requirements and enabling lower NOx production. Evaluating components and subcomponents fabricated from these advanced CMCs under gas turbine conditions is paramount to demonstrating that the material system can perform as required in the complex thermal stress and environmentally aggressive engine environment. To date, only limited testing has been conducted on CMC combustor and turbine concepts and subelements of this type throughout the industry. As part of the Ultra-Efficient Engine Technology (UEET) Program, the High Pressure Burner Rig (HPBR) at the NASA Glenn Research Center was selected to demonstrate coupon, subcomponent feature, and component testing because it can economically provide the temperatures, pressures, velocities, and combustion gas compositions that closely simulate the engine environments. The results have proven the HPBR to be a highly versatile test rig amenable to multiple test specimen configurations essential to coupon and component testing.

Roinson, R. Craig↗
DOE OSTI2026

Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method

Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Jet classification using high-level features from anatomy of top jets

Recent advancements in deep learning models have significantly enhanced jet classification performance by analyzing low-level features (LLFs). However, this approach often leads to less interpretable models, emphasizing the need to understand the decision-making process and to identify the high-level features (HLFs) crucial for explaining jet classification. To address this, we consider the top jet tagging problems and introduce an analysis model (AM) that analyzes selected HLFs designed to capture important features of top jets. Our AM mainly consists of the following three modules: a relation network analyzing two-point energy correlations, mathematical morphology and Minkowski functionals for generalizing jet constituent multiplicities, and a recursive neural network analyzing subjet constituent multiplicity to enhance sensitivity to subjet color charges. We demonstrate that our AM achieves performance comparable to the Particle Transformer (ParT) while requiring fewer computational resources in a comparison of top jet tagging using jets simulated at the hadronic calorimeter angular resolution scale. Furthermore, as a more constrained architecture than ParT, the AM exhibits smaller training uncertainties because of the bias-variance tradeoff. We also compare the information content of AM and ParT by decorrelating the features already learned by AM. Lastly, we briefly comment on the results of AM with finer angular resolution inputs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗