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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Overview of NASA Electrified Aircraft Propulsion Research for Large Subsonic Transports

NASA is investing in Electrified Aircraft Propulsion (EAP) research as part of the portfolio to improve the fuel efficiency, emissions, and noise levels in commercial transport aircraft. Turboelectric, partially turboelectric, and hybrid electric propulsion systems are the primary EAP configurations being evaluated for regional jet and larger aircraft. The goal is to show that one or more viable EAP concepts exist for narrow body aircraft and mature tall-pole technologies related to those concepts. A summary of the aircraft system studies, technology development, and facility development is provided. The leading concept for mid-term (2035) introduction of EAP for a single aisle aircraft is a tube and wing, partially turbo electric configuration (STARC-ABL), however other viable configurations exist. Investments are being made to raise the TRL level of light weight, high efficiency motors, generators, and electrical power distribution systems as well as to define the optimal turbine and boundary layer ingestion systems for a mid-term tube and wing configuration. An electric aircraft power system test facility (NEAT) is under construction at NASA Glenn and an electric aircraft control system test facility (HEIST) is under construction at NASA Armstrong. The correct building blocks are in place to have a viable, large plane EAP configuration tested by 2025 leading to entry into service in 2035 if the community chooses to pursue that goal.

Jansen, Ralph H.↗
NASA NTRS2017

Overview of NASA Electrified Aircraft Propulsion Research for Large Subsonic Transports

NASA is investing in Electrified Aircraft Propulsion (EAP) research as part of the portfolio to improve the fuel efficiency, emissions, and noise levels in commercial transport aircraft. Turboelectric, partially turboelectric, and hybrid electric propulsion systems are the primary EAP configurations being evaluated for regional jet and larger aircraft. The goal is to show that one or more viable EAP concepts exist for narrow body aircraft and mature tall-pole technologies related to those concepts. A summary of the aircraft system studies, technology development, and facility development is provided. The leading concept for mid-term (2035) introduction of EAP for a single aisle aircraft is a tube and wing, partially turbo electric configuration (STARC-ABL), however other viable configurations exist. Investments are being made to raise the TRL level of light weight, high efficiency motors, generators, and electrical power distribution systems as well as to define the optimal turbine and boundary layer ingestion systems for a mid-term tube and wing configuration. An electric aircraft power system test facility (NEAT) is under construction at NASA Glenn and an electric aircraft control system test facility (HEIST) is under construction at NASA Armstrong. The correct building blocks are in place to have a viable, large plane EAP configuration tested by 2025 leading to entry into service in 2035 if the community chooses to pursue that goal.

aircraft engines↗
NASA NTRSDate not supplied

Artificial Neural Networks to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗
NASA NTRSDate not supplied

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗
DOE OSTI2020

Power Density Waterfalls Plots for AGR-1, AGR-2 US UCO, and AGR-5/6/7 Experiments

Task: Generate plots of the distribution of power per particle per power bin over time. Kairos needs these for licensing purposes. Basically, they need to know which power/particle was sustained by which fraction of the fuel and for how long. The idea is to leverage AGR results. However, Kairos wants to operate at relatively high power/particle and, therefore, they need to check how much of their range is covered by AGR. These plots are made for AGR-1, AGR-2 US UCO, and what is predicted for AGR-5/6 and AGR-7 (for which there are no daily as-run values but projected values for every cycle). The predicted AGR-5/6/7 data was provided by the attached Excel file in an Email by Blaise Collin to Cam Binh Pham on May 21, 2018.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Modeling the Interaction Between Energy Efficiency and Demand Response on Regional Grid Scales: Preprint

With increasing penetration of intermittent renewable generation at grid and distributed scales, flexible building loads can provide significant system value and support the evolving needs of the grid. The growing value of load flexibility may complicate the traditional separation between energy efficiency (EE) and demand response (DR). EE measures may compete in some cases with a building’s DR capabilities but complement one another in other cases. EE can also increase or decrease the need for DR at the system level and change the availability of DR to meet system needs. In this study we present a bottom-up approach to modeling interactive effects between EE and DR in buildings within two regions of the US electricity grid. From a library of building simulation models for different buildings and climates, we synthesize system-level demand profiles and the impacts of potential future EE portfolios. Coupling the underlying building models with a database of DR-enabling technologies, we then compute the quantity of DR that can be delivered in each scenario. The results show that EE and DR interactions are largely driven by the timing of EE savings that are measure-specific and the coincidence with system peak demand that is region-specific. We also find that perspective of the impacts matters – for instance that some EE measures reduce the system need for DR but also reduce the DR potential. Our results imply that utility EE and DR programs developed without considering interactive effects may lead to increased grid-management challenges over the long term.

buildings↗
DOE OSTI2022

Black Start From DER

This presentation gives overview of black start related research at NREL.

black start↗
DOE OSTI2023

Methods and systems for evaluating data transportability in distribution grids

This document describes systems and techniques for evaluating and improving distribution-grid data transportability. These systems and techniques allow engineers to quantify the data transportability of a communication system within or connected to a distribution grid, which represents an ability to transport in real-time telemetry from source locations (e.g., sensors in the distribution grid) to control mechanisms. Distribution engineers can use the sensor readings to perform grid analytics, control operating parameters, and operate protection systems. Distribution engineers can also use the transportability of the communication system to evaluate the observability of the distribution grid, which represents an ability to combine actual measurements and various types of computations (e.g., analytics, estimators, forecasters) from a system model. Distribution engineers can then generate a sensor allocation plan that indicates the number and location of sensors to maximize observability for a fixed sensor cost and/or minimize sensor cost for predetermined observability.

Taft, Jeffrey D.↗
DOE OSTI2025

Unfolding Structure Formation in the Dark Universe via Weak Gravitational Lensing: from Pixels to Cosmology in the Dark Energy Survey and Roman Space Telescope

Weak gravitational lensing (deflection of light from distant galaxies due to the gravitational potential of intervening mass) is one of the most exciting probes in cosmology as it is sensitive both to the growth of the large-scale structure and the expansion history of the Universe. We can measure the coherent distortion of galaxy shapes (which we call cosmic shear) and infer the matter distribution. With next-generation imaging surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (Rubin LSST) and the Nancy G. Roman Space Telescope (Roman), there is immense new promise in understanding the fundamental nature of dark matter and dark energy. With datasets from current experiments like the Dark Energy Survey (DES), we see apparent cosmological tensions between experiments that may either be real and indicate new physics or new systematics we do not yet understand. LSST and Roman will increase the number of galaxies we have observed by an order of magnitude, leading to improved constraints on our cosmological model by up to 300%. These experiments will have the potential to prove if these cosmological tensions are real. However, our control of systematic uncertainties must also improve by similar levels to achieve the promise of what these missions can deliver. To achieve these scientific outcomes, the challenges of determining galaxy shapes and redshifts and modeling the impact of astrophysical effects must be solved. My PhD has focused on enabling weak lensing science in DES and Roman. I co-led the shear analysis teams in DES to produce the largest weak lensing galaxy sample, as well as the final DES cosmological analysis of cosmic shear. For Roman, I have led two papers characterizing and mitigating shear-related systematics with image simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

PHOTOPRODUCTION OF np^0 BY DOUBLE-REGGE EXCHANGE

The GlueX experiment is a photoproduction experiment based at Jeferson Lab in Newport News, Virginia. A major aim of GlueX is to look for hybrid mesons, which are a quark and an anti-quark bound by an excited gluonic field that contributes to the quantum numbers. The reaction ¿p ¿ ¿e0p is of particular interest since ¿e is a potential decay mode of states with exotic quantum numbers JPC =1¿+, which are forbidden in the constituent quark model. Finding such a resonance would be a clear sign of non-quark model physics. In concert with the Joint Physics Analysis Center we have developed a model for double-Regge interactions in this channel. These non-resonant processes generate asymmetries in the distributions of decay angles, which could be falsely attributed to the interference between exotic odd partial waves and even partial waves. In previous searches for light exotics we have seen evidence for the necessity of accounting for the presence of these non-resonant productions. We present a double-Regge model for photoproduction of ¿e0 and the application of it by measuring the asymmetry of ¿e0 production in the double Regge limit, as well as a comparison of the measured results to current theoretical predictions.

Barsotti, Rebecca [Indiana Univ. Southeast, New Al↗
NASA NTRS1984

Whistler mode turbulence generated by electron beams in earth's bow shock

The Landau and cyclotron growth rates of whistler mode waves in the earth's bow shock are calculated by using electron distribution functions obtained with the fast plasma experiment on ISEE 2. Three electron distribution functions measured within the transition region of the shock are analyzed. These functions spontaneously generate whistler mode waves with plasma rest frame frequencies between about 0.1 and 100 Hz. The wave normal angles of the generated whistlers range from 0 deg to the resonance cone angle. Electromagnetic Landau resonance and/or cyclotron resonance contribute to wave growth over the range of observed velocity distributions. Waves generated by the normal cyclotron resonance have wave vectors directed toward the solar wind, while those generated by the Landau and the anomalous cyclotron resonances have vectors directed toward the magnetosheath. The preditions of the study are in qualitative agreement with observations of whistler mode waves near the earth's bow shock.

Tokar, R. L.↗
NASA NTRS1978

Three-dimensional plasma measurements within the earth's magnetosphere

Magnetospheric measurements of three-dimensional velocity distributions for positive ions and electrons in the energy range from 1 eV to 45 keV are reported which were obtained with quadrispherical Lepedeas on ISEE 1 and 2. The instrumentation is briefly described, and an extension of energy-time spectrograms to three-dimensional summaries via the use of ancillary energy-spin phase spectrograms for multiple analyzers is outlined. Macroscopic plasma parameters for two crossings of the dayside magnetopause are presented, along with a preliminary evaluation of the kinematical motions of low-energy charged particles within the terrestrial ring current. Nonmonotonic electron velocity distributions presumably related to the generation of electron cyclotron harmonic instabilities are examined. The possible signature of diffusion driven by electrostatic waves is considered, and velocity distributions of positive ions in the dawn magnetotail are investigated.

Frank, L. A.↗
DOE OSTI2020

Transition radiation light sources

Transition radiation from nanotubes, nanosheets, and nanoparticles and in particular, boron nitride nanomaterials, can be utilized for the generation of light. Wavelengths of light of interest for microchip lithography, including 13.5 nm (91.8 eV) and 6.7 nm (185 eV), can be generated at useful intensities, by transition radiation light sources. Light useful for monitoring relativistic charged particle beam characteristics such as spatial distribution and intensity can be generated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Transition radiation light sources

Transition radiation from nanotubes, nanosheets, and nanoparticles and in particular, boron nitride nanomaterials, can be utilized for the generation of light. Wavelengths of light of interest for microchip lithography, including 13.5 nm (91.8 eV) and 6.7 nm (185 eV), can be generated at useful intensities, by transition radiation light sources. Light useful for monitoring relativistic charged particle beam characteristics such as spatial distribution and intensity can be generated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Beam halo formation with different cathode distributions

Beam halo refers to the low-density distribution of particles extending beyond the beam core, and its generation and mitigation are important topics in particle accelerator design. Effective mitigation of beam halo is essential for the cooler design based on Energy Recovery Linac (ERL), which must deliver an electron beam with average beam current of 100 mA and a charge 1 nC per bunch. In the ERL injector and booster linacs, space charge effects are stronger due to relatively low beam energy (6 MeV). Additionally, the longer bunch length of approximately 100 ps in this regime vs the RF period of 5.08 ns makes the formation of beam halos more likely. Therefore, effective collimation of beam halo is critical to maintaining the required beam parameters. To design an effective collimation scheme, several halo distributions were generated at the cathode and used to study halo formation within the injector-merger. This paper presents different halo distributions and halo formation, providing insights on halo collimation strategy.

Accelerator Physics↗
NASA NTRS1975

A distributed data base management system

Major system design features of a distributed data management system for the NASA Deep Space Network (DSN) designed for continuous two-way deep space communications are described. The reasons for which the distributed data base utilizing third-generation minicomputers is selected as the optimum approach for the DSN are threefold: (1) with a distributed master data base, valid data is available in real-time to support DSN management activities at each location; (2) data base integrity is the responsibility of local management; and (3) the data acquisition/distribution and processing power of a third-generation computer enables the computer to function successfully as a data handler or as an on-line process controller. The concept of the distributed data base is discussed along with the software, data base integrity, and hardware used. The data analysis/update constraint is examined.

Bryan, A. I.↗