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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 523 records · Page 29

Transitions in the morphology and critical stresses of gliding dislocations in multiprincipal element alloys

Refractory multiprincipal element alloys (MPEAs) are promising material candidates for high-temperature, high-strength applications. However, their deformation mechanisms, particularly at the dislocation scale, are unusual compared to those of conventional alloys, making it challenging to understand the origin of their high strength. Here, using an atomistically informed phase-field dislocation dynamics model, we study transitions in the morphology and critical stresses of long gliding screw dislocations over extended distances in a refractory MPEA. The model MPEA crystal accounts for the atomic-scale fluctuations in chemical composition across the glide planes via spatially correlated lattice energies and for the differences in glide resistances between screw and edge dislocations of unit length. Here, we show that the dislocation moves in a stop-start motion, alternating between wavy morphology in free flight and nearly recovered straight screw orientation in full arrest. The periods of wavy glide are due to variable kink-pair formation and migration rates along the length, where portions with higher rates glide more quickly. The critical stress to initiate motion corresponds to the stress required to form and migrate a kink pair at the weakest region along the length of the dislocation. Heterogeneity in lattice energy leads to variability in the local stress-strain response and to a strain hardening-like response, in which the critical stress to reactivate glide increases with glide distance. Statistical assessment of hundreds of realizations of dislocations indicates that the amount of hardening directly scales with the dispersion in underlying lattice energy.

3-dimensional systems↗

Commissioning of a Cask Enabling Characterization of Irradiated Nuclear Fuels with Pulsed Neutrons

Irradiation tests are a key component of nuclear fuel development and identifying typical and atypical regions in the irradiated fuel volume relies on very few characterization techniques. The goal of the effort reported here is to provide complementary measurements adding to the available parameter space for post irradiation examination as well as to inform subsequent hot cell PIE examinations by identifying typical and atypical regions with respect to microstructure, tomographic data, or isotope densities. Pulsed neutrons, enabling diffraction as well as energy-resolved neutron imaging and neutron absorption resonance spectroscopy, offer unique capabilities for this purpose. Time-of-flight neutron diffraction has the potential to offer efficient, non-destructive and non-contact microstructural characterization of irradiated fuel pins with spatial resolution of 1 mm 3 to 1 cm 3 while for energy-resolved neutron imaging (and by extension tomography) a resolution of 100 μm was demonstrated. The potential results include crystallinity vs. amorphous volumes and microstructural information such as phase compositions, lattice strains (indicative of residual stresses or chemistry variations) and textures from the diffraction data as well as distances (e.g. pellet to cladding), cracks, and isotopic distributions of minor actinides, fission products as well as fission gas partial pressures e.g. in the plenum from energy resolved neutron imaging.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Progress Report on Mockup Irradiation Capsule Fuel Measurements at LANSCE

Irradiation tests are a key component of nuclear fuel development and identifying typical and atypical regions in the irradiated fuel volume relies on very few characterization techniques. The goal of the effort reported here is to provide complementary measurements adding to the available parameter space for post irradiation examination as well as to inform subsequent hot cell PIE examinations by identifying typical and atypical regions with respect to microstructure, tomographic data, or isotope densities. Pulsed neutrons, enabling diffraction as well as energy-resolved neutron imaging and neutron absorption resonance spectroscopy, offer unique capabilities for this purpose. Time-of-flight neutron diffraction has the potential to offer efficient, non-destructive and non-contact microstructural characterization of irradiated fuel specimen with spatial resolution of 1 mm 3 to 1 cm 3 while for energy-resolved neutron imaging (and by extension tomography) a resolution of 100 μm 3 was demonstrated. The potential results include crystallinity vs. amorphous volumes and microstructural information such as phase compositions, lattice strains (indicative of residual stresses or chemistry variations) and textures from the diffraction data as well as distances (e.g. pellet to cladding), cracks, and isotope densities of minor actinides, fission products as well as fission gas partial pressures e.g. in the plenum from energy resolved neutron imaging.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Constraints on extragalactic-jet characteristics from lobe observations

Very Large Array spectral and polarimetric observations of the lobes of luminous, double radio galaxies are discussed. These observations can provide information on the jets responsible for the sources. Spectral steepening is usually observed in the lobes, with the radio spectral index increasing with distance from the hot spot. These data can be used to infer a 'speed of separation' of the hot spot and lobe material. These speeds are in agreement with hydrocode models of jets. Polarimetric observations indicate that in at least some sources, there is an undectably small amount of internal Faraday rotation, indicating upper limits to the thermal-plasma density of a few times 10 to the -5th/cu cm or less. These measurements are also in agreement with the numerical beam models, provided that the beam density is substantially less than that of the background medium. It is concluded that the lobe observations indicate that these sources are powered by light, high-Mach-number beams.

Spangler, S. R.↗

Stereoscopic Optical Signal Processor

Optical signal processor produces two-dimensional cross correlation of images from steroscopic video camera in real time. Cross correlation used to identify object, determines distance, or measures movement. Left and right cameras modulate beams from light source for correlation in video detector. Switch in position 1 produces information about range of object viewed by cameras. Position 2 gives information about movement. Position 3 helps to identify object.

Graig, Glenn D.↗

Pioneer 8 traversal of the geomagnetic tail at 1600 R(E)

The Pioneer 8 spacecraft (launched on December 13, 1967) first crossed the geomagnetic tail at a downstream distance of 500-800 R(E) as it left the earth-moon system, and during a two-week period centered on January 23, 1968, the magnetometer, plasma probe and plasma wave instrument all detected specific tail-related phenomena. In April and May of 1985, Pioneer 8 traversed the expected position of the earth's tail once again, at an average downstream distance of 1650 R(E). This report contains a summary of the 1985 Pioneer 8 measurements, and a brief discussion of the limited information available on solar wind variations and terrestrial magnetic activity indicators.

Scarf, Frederick L.↗

Improving the geometric fidelity of imaging systems employing sensor arrays

A sensor assembly to be carried on an aircraft or spacecraft which will travel along an arbitrary flight path, for providing an image of terrain over which the craft travels, is disclosed. The assembly includes a main linear sensor array and a plurality of auxiliary sensor arrays oriented parallel to, and at respectively different distances from, the main array. By comparing the image signals produced by the main sensor array with those produced by each auxiliary array, information relating to variations in velocity of the craft carrying the assembly can be obtained. The signals from each auxiliary array will provide information relating to a respectively different frequency range.

Jones, Kenneth L.↗

Microprobe studies of microtomed particles of white druse salts in shergottite EETA 79001

The white druse material in Antarctic shergottite EETA 79001 has attracted much attention as a possible sample fo Martian aqueous deposits. Instrumental Neutron Activation Analysis (INAA) was used to determine trace element analyses of small particles of this material obtained by handpicking of likely grains from broken surfaces of the meteorite. Electron microprobe work was attempted on grain areas as large as 150x120 microns. Backscattered electron images show considerable variations in brightness, and botryoidal structures were observed. Microprobe analyses showed considerable variability both within single particles and between different particles. Microtomed surfaces of small selected particles were shown to be very useful in obtaining information on the texture and composition of rare lithologies like the white druse of EETA 79001. This material is clearly heterogeneous on all distance scales, so a large number of further analyses will be required to characterize it.

Lindstrom, D. J.↗

Determining the Loci of Anomalies Using Minimal Causal Models

A new technique is described for attention focusing for use in anomaly detection in complex physical systems. The technique involves reasoning about the distance between two frequency distributions, and it is used to detect both anomalous system parameters and 'broken' causal dependencies. These two forms of information together isolate the locus of anomalous behavior in the system being monitored.

qualitative reasoning naive physics causal reasoni↗

Geometric fiedlity of imaging systems employing sensor arrays

A sensor assembly to be carried on an aircraft or spacecraft which will travel along an arbitrary flight path, for providing an image of terrain over which the craft travels. The assembly includes a main linear sensor array and a plurality of auxiliary sensor arrays oriented parallel to, and at respectively different distances from, the main array. By comparing the image signals produced by the main sensor array with those produced by each auxiliary array, information relating to variations in velocity of the craft carrying the assembly can be obtained. The signals from each auxiliary array will provide information relating to a respectively different frequency range.

Jones, Kenneth L.↗

The Formation Heritage of Jupiter Family Comet 10P/Tempel 2 as Revealed by Infrared Spectroscopy

We present spectral and spatial information for major volatile species in Comet 10P/Tempel 2, based on high-dispersion infrared spectra acquired on UT 2010 July 26 (heliocentric distance R h = 1.44 AU) and September 18 (R h = 1.62 AU), following the comet’s perihelion passage on UT 2010 July 04. The total production rate for water on July 26 was (1.90 ± 0.12) × 10 28 molecules s −1 , and abundances of six trace gases (relative to water) were: CH 3 OH (1.58% ± 0.23%), C 2 H 6 (0.39% ± 0.04%), NH 3 (0.83% ± 0.20%), and HCN (0.13% ± 0.02%). A detailed analysis of intensities for water emission lines provided a rotational temperature of 35 ± 3 K. The mean OPR is consistent with nuclear spin populations in statistical equilibrium (OPR = 3.01 ± 0.18), and the (1σ) lower bound corresponds to a spin temperature >38 K. Our measurements were contemporaneous with a jet-like feature observed at optical wavelengths. The spatial profiles of four primary volatiles display strong enhancements in the jet direction, which favors release from a localized vent on the nucleus. The measured IR continuum is much more sharply peaked and is consistent with a dominant contribution from the nucleus itself. The peak intensities for H 2 O, CH 3 OH, and C 2 H 6 are offset by ∼200 km in the jet direction, suggesting the possible existence of a distributed source, such as the release of icy grains that subsequently sublimed in the coma. On UT September 18, no obvious emission lines were present in our spectra, nevertheless we obtained a 3σ upper limit Q(H 2 O) < 2.86 × 10 27 molecules s −1 .

Organic Chemistry↗

Sense and Avoid Characterization of the Independent Configurable Architecture for Reliable Operations of Unmanned Systems

Abstract—Independent Configurable Architecture for Reliable Operations of Unmanned Systems (ICAROUS) is a distributed software architecture developed by NASA Langley Research Center to enable safe autonomous UAS operations. ICAROUS consists of a collection formally verified core algorithms for path planning, traffic avoidance, geofence handling, and decision making that interface with an autopilot system through a publisher-subscriber middleware. The ICAROUS Sense and Avoid Characterization (ISAAC) test was designed to evaluate the performance of the onboard Sense and Avoid (SAA) capability to detect potential conflicts with other aircraft and autonomously maneuver to avoid collisions, while remaining within the airspace boundaries of the mission. The ISAAC tests evaluated the impact of separation distances and alerting times on SAA performance. A preliminary analysis of the effects of each parameter on key measures of performance is conducted, informing the choice of appropriate parameter values for different small Unmanned Aircraft Systems (sUAS) applications. Furthermore, low-power Automatic Dependent Surveillance – Broadcast (ADS-B) is evaluated for potential use to enable autonomous sUAS to sUAS deconflictions as well as to provide usable warnings for manned aircraft without saturating the frequency spectrum.

Consiglio, Maria↗

The Atacama Cosmology Telescope: DR4 maps and cosmological parameters

We present new arcminute-resolution maps of the Cosmic Microwave Background temperature and polarization anisotropy from the Atacama Cosmology Telescope, using data taken from 2013{2016 at 98 and 150 GHz. The maps cover more than 17,000 deg(^2), the deepest 600 deg(^2) with noise levels below 10µK-arcmin. We use the power spectrum derived from almost 6,000 deg(^2) of these maps to constrain cosmology. The ACT data enable a measurement of the angular scale of features in both the divergence-like polarization and the temperature anisotropy, tracing both the velocity and density at last-scattering. From these one can derive the distance to the last-scattering surface and thus infer the local expansion rate, H0. By combining ACT data with large-scale information from WMAP we measure H0 = 67:6±1:1 km/s/Mpc, at 68% confidence, in excellent agreement with the independently measured Planck satellite estimate (from ACT alone we find H0 = 67:9± 1:5 km/s/Mpc). The ΛCDM model provides a good fit to the ACT data, and we find no evidence for deviations: both the spatial curvature, and the departure from the standard lensing signal in the spectrum, are zero to within 1σ; the number of relativistic species, the primordial Helium fraction, and the running of the spectral index are consistent with ΛCDM predictions to within 1.5{2.2σ. We compare ACT, WMAP, and Planck at the parameter level and find good consistency; we investigate how the constraints on the correlated spectral index and baryon density parameters readjust when adding CMB large-scale information that ACT does not measure. The DR4 products presented here will be publicly released on the NASA Legacy Archive for Microwave Background Data Analysis.

Simone Aiola↗

Hazard-Based Model of Activity Generation Using Vehicle Trajectory Data

Travel behavior modeling suffers from lack of longitudinal data due to the high cost of procurement and difficulty with ensuring data quality. In the recent years ubiquitous data intercepted from social media, cell detail record, GPS traces are increasingly being explored to analyze human mobility. However, these data lack key demographic information which limits their use for developing causal models of traveler behavior. The primary contribution of the paper lies in using vehicle trajectory data from Ann Arbor along with multiple other data sources for developing a hazard-based activity generation model. The different category of data used in the analysis include (i) vehicle trajectory data (VTD), (ii) American Census Survey (ACS), (iii) land use data, (iv) household travel survey (HTS) data, and (v) smart location data from Environmental Protection Agency (EPA). Home and work are identified as the two most frequently visited locations from the VTD and validated against land use categories of the region. Next a random utility-based model is developed using HTS data to identify other activity purposes as a function of the polynomials of distance from home, activity duration and departure time. The developed model is then applied to identify the non-home activity purposes in the VTD. Demographic and accessibility information are appended to the VTD from ACS and smart location databases respectively. The fmal database is then used to develop a hazard-based activity generation model. (C) 2020 The Authors. Published by Elsevier B.V.

activity generation↗

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗

Infrared Sensor on Unmanned Aircraft Transmits Time-Critical Wildfire Data

Since 2006, NASA fs Dryden Flight Research Center (DFRC) and Ames Research Center have been perfecting and demonstrating a new capability for geolocation of wildfires and the real-time delivery of data to firefighters. Managed for the Western States Fire Mission, the Ames-developed Autonomous Modular Scanner (AMS), mounted beneath a wing of DFRC fs MQ-9 Ikhana remotely piloted aircraft, contains an infrared sensor capable of discriminating temperatures within 0.5 F (approx. = 0.3 C), up to 1,000 F (approx. = 540 C). The AMS operates like a digital camera with specialized filters to detect light energy at visible, infrared, and thermal wavelengths. By placing the AMS aboard unmanned aircraft, one can gather information and imaging for thousands of square miles, and provide critical information about the location, size, and terrain around fires to commanders in the field. In the hands of operational agencies, the benefits of this NASA research and development effort can support nationwide wildfire fighting efforts. The sensor also provides data for post-burn and vegetation regrowth analyses. The MQ-9 Unmanned Aircraft System (UAS), a version of the Predator-B, can operate over long distances, staying aloft for over 24 hours, and controlled via a satellite-linked command and control system. This same link is used to deliver the fire location data directly to fire incident commanders, in less than 10 minutes from the time of overflight. In the current method, similarly equipped short-duration manned aircraft, with limited endurance and range, must land, hand-carry, and process data, and then deliver information to the firefighters, sometimes taking several hours in the process. Meanwhile, many fires would have moved over great distances and changed direction. Speed is critical. The fire incident commanders must assess a very dynamic situation, and task resources such as people, ground equipment, and retardant-dropping aircraft, often in mountainous terrain obscured by dense smoke.

Pestana, Mark↗

Geometrical defect detection for additive manufacturing with machine learning models

This study proposed a scheme based on Machine Learning (ML) models to detect geometric defects of additively manufactured objects. The ML models are trained with synthetic 3D point clouds with defects and then applied to detect defects in actual production. Using synthetic 3D point clouds rather than experimental data could save a huge amount of training time and costs associated with many prints for each design. Besides distance differences of individual points between source and target point clouds, this scheme uses a new concept called “patch” to capture macro-level information about nearby points for ML training and implementation. Numerical comparisons of prediction results on experimental data with different shapes showed that the proposed scheme outperformed the existing Z-difference method in the literature. Five ML methods (Bagging of Trees, Gradient Boosting, Random Forest, K-nearest Neighbors and Linear Supported Vector Machine) were compared under various conditions, such as different point cloud densities and defect sizes. Bagging and Random Forest were found the two best models regarding predictability; and the right patch size was found to be at 20. The proposed ML-based scheme is applicable to in-situ defect detection during additive manufacturing with the aid of a proper 3D data acquisition system.

Additive manufacturing↗

Patch selection by bumble bees navigating discontinuous landscapes

Pollen and nectar resources are unevenly distributed over space and bees must make routing decisions when navigating patchy resources. Determining the patch selection process used by bees is crucial to understanding bee foraging over discontinuous landscapes. To elucidate this process, we developed four distinct probability models of bee movement where the size and the distance to the patch determined the attractiveness of a patch. A field experiment with a center patch and four peripheral patches of two distinct sizes and distances from the center was set up in two configurations. Empirical transition probabilities from the center to each peripheral patch were obtained at two sites and two years. The best model was identified by comparing observed and predicted transition probabilities, where predicted values were obtained by incorporating the spatial dimensions of the field experiment into each model’s mathematical expression. Bumble bees used both patch size and isolation distance when selecting a patch and could assess the total amount of resources available in a patch. Bumble bees prefer large, nearby patches. This information will facilitate the development of a predictive framework to the study of bee movement and of models that predict the movement of genetically engineered pollen in bee-pollinated crops.

54 ENVIRONMENTAL SCIENCES↗