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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 253 records · Page 14

Design of a robot-automated flat plate/reflection geometry x-ray diffraction setup for accelerated materials discovery and structural screening

Here, we report the design, construction, and automation of a flat plate sample loading, alignment, and data acquisition system for X-ray diffraction measurements in reflection geometry implemented at the Stanford Synchrotron Radiation Lightsource. The system is built onto a single platform, enabling facile transferability, and is compartmentalized into sample storage, sample transfer, and sample position/alignment segments. The core feature of this system is a six-axis robotic arm that offers a large range of highly reproducible and programable movements. The degrees of freedom of the robot arm enable adaptability in which movements can be modified to fit various beamline environments and sample configurations. Samples are housed on 3D printed sample mounts, which are arranged onto a 6 × 2 array of sample cassettes capable of holding 7 samples. Using sample mounts designed for solid oxide electrolysis button cells (SOECs), the maximum tray capacity is 84 samples, which can be aligned and run in ~ 24 hours with long exposure scans. The sample array is additionally capable of accommodating a range of sample sizes and geometries due to the rapid 3D printed fabrication. The components of the setup will be described in detail and performance will be demonstrated with a set of representative SOEC and XRD standard samples. Opportunities for future developments and integration with the automated setup are summarized.

08 HYDROGEN↗

NASA Tech Briefs, May 2008

Topics covered inclde: Deployable Wireless Camera Penetrators; Hand-Held Units for Short-Range Wireless Biotelemetry; Wearable Wireless Telemetry System for Implantable BioMEMS Sensors; Electronic Escape Trails for Firefighters; Architecture for a High-to-Medium-Voltage Power Converter; 24-Way Radial Power Combiner/Divider for 31 to 36 GHz; Three-Stage InP Submillimeter-Wave MMIC Amplifier; Fast Electromechanical Switches Based on Carbon Nanotubes; Solid-State High-Temperature Power Cells; Fast Offset Laser Phase-Locking System; Fabricating High-Resolution X-Ray Collimators; Embossed Teflon AF Laminate Membrane Microfluidic Diaphragm Valves; Flipperons for Improved Aerodynamic Performance; System Estimates Radius of Curvature of a Segmented Mirror; Refractory Ceramic Foams for Novel Applications; Self-Deploying Trusses Containing Shape-Memory Polymers; Fuel-Cell Electrolytes Based on Organosilica Hybrid Proton Conductors; Molecules for Fluorescence Detection of Specific Chemicals; Cell-Detection Technique for Automated Patch Clamping; Redesigned Human Metabolic Simulator; Compact, Highly Stable Ion Atomic Clock; LiGa(OTf)(sub 4) as an Electrolyte Salt for Li-Ion Cells; Compact Dielectric-Rod White-Light Delay Lines; Single-Mode WGM Resonators Fabricated by Diamond Turning; Mitigating Photon Jitter in Optical PPM Communication; MACOS Version 3.31; Fiber-Optic Determination of N2, O2, and Fuel Vapor in the Ullage of Liquid-Fuel Tanks; Spiking Neurons for Analysis of Patterns; Symmetric Phase-Only Filtering in Particle-Image Velocimetry; Efficient Coupler for a Bessel Beam Dispersive Element; and Attitude and Translation Control of a Solar Sail Vehicle.

Source record↗

A new method for recognizing quadric surfaces from range data and its application to telerobotics and automation, final phase

In the final phase of the proposed research a complete top to down three dimensional object recognition scheme has been proposed. The various three dimensional objects included spheres, cones, cylinders, ellipsoids, paraboloids, and hyperboloids. Utilizing a newly developed blob determination technique, a given range scene with several non-cluttered quadric surfaces is segmented. Next, using the earlier (phase 1) developed alignment scheme, each of the segmented objects are then aligned in a desired coordinate system. For each of the quadric surfaces based upon their intersections with certain pre-determined planes, a set of distinct features (curves) are obtained. A database with entities such as the equations of the planes and angular bounds of these planes has been created for each of the quadric surfaces. Real range data of spheres, cones, cylinders, and parallelpipeds have been utilized for the recognition process. The developed algorithm gave excellent results for the real data as well as for several sets of simulated range data.

Mielke, Roland↗

Computer-implemented system and method for automated and highly accurate plaque analysis, reporting, and visualization

A computer-implemented system and method of intra-oral analysis for measuring plaque removal is disclosed. The system includes hardware for real-time image acquisition and software to store the acquired images on a patient-by-patient basis. The system implements algorithms to segment teeth of interest from surrounding gum, and uses a real-time image-based morphing procedure to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The system integrates these components into a single software suite with an easy-to-use graphical user interface (GUI) that allows users to do an end-to-end run of a patient record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image.

Kemp, James Herbert↗

AUTOFLOW enhancements for documentation and maintenance of scientific applications

The use of the AUTOFLOW system is discussed in terms of improving automated documentation. Flowcharts produced by AUTOFLOW are considered to be much more meaningful than those produced manually in that they are accurate, present complete references between all transfer points, and graphically portray the logical flow by automatic rearrangement of those segments of the program that interact.

Goetz, M. A.↗

Field study of communication and workload in police helicopters - Implications for AI cockpit design

This paper reports on the work performed by civilian helicopter crews, using audio and video recordings and a variety of workload measures (heart rate and subjective ratings) obtained in a field study of public service helicopter missions. The number and frequency of communications provided a significant source of workload. This is relevant to the design of automated cockpit systems, since many designs presuppose the use of voice I/O systems. Fluency of communications (including pauses, hesitation markers, repetitions, and false starts) furnished an early indication of the effects of fatigue. Three workload measures were correlated to identify high workload segments of flight, and to suggest alternate task allocations between crew members.

Linde, Charlotte↗

Scheduling with Automatic Resolution of Conflicts

DSN Requirement Scheduler is a computer program that automatically schedules, reschedules, and resolves conflicts for allocations of resources of NASA s Deep Space Network (DSN) on the basis of ever-changing project requirements for DSN services. As used here, resources signifies, primarily, DSN antennas, ancillary equipment, and times during which they are available. Examples of project-required DSN services include arraying, segmentation, very-long-baseline interferometry, and multiple spacecraft per aperture. Requirements can include periodic reservations of specific or optional resources during specific time intervals or within ranges specified in terms of starting times and durations. This program is built on the Automated Scheduling and Planning Environment (ASPEN) software system (aspects of which have been described in previous NASA Tech Briefs articles), with customization to reflect requirements and constraints involved in allocation of DSN resources. Unlike prior DSN-resource- scheduling programs that make single passes through the requirements and require human intervention to resolve conflicts, this program makes repeated passes in a continuing search for all possible allocations, provides a best-effort solution at any time, and presents alternative solutions among which users can choose.

Clement, Bradley↗

Hexagonal Pixels and Indexing Scheme for Binary Images

A scheme for resampling binaryimage data from a rectangular grid to a regular hexagonal grid and an associated tree-structured pixel-indexing scheme keyed to the level of resolution have been devised. This scheme could be utilized in conjunction with appropriate image-data-processing algorithms to enable automated retrieval and/or recognition of images. For some purposes, this scheme is superior to a prior scheme that relies on rectangular pixels: one example of such a purpose is recognition of fingerprints, which can be approximated more closely by use of line segments along hexagonal axes than by line segments along rectangular axes. This scheme could also be combined with algorithms for query-image-based retrieval of images via the Internet. A binary image on a rectangular grid is generated by raster scanning or by sampling on a stationary grid of rectangular pixels. In either case, each pixel (each cell in the rectangular grid) is denoted as either bright or dark, depending on whether the light level in the pixel is above or below a prescribed threshold. The binary data on such an image are stored in a matrix form that lends itself readily to searches of line segments aligned with either or both of the perpendicular coordinate axes. The first step in resampling onto a regular hexagonal grid is to make the resolution of the hexagonal grid fine enough to capture all the binaryimage detail from the rectangular grid. In practice, this amounts to choosing a hexagonal-cell width equal to or less than a third of the rectangular- cell width. Once the data have been resampled onto the hexagonal grid, the image can readily be checked for line segments aligned with the hexagonal coordinate axes, which typically lie at angles of 30deg, 90deg, and 150deg with respect to say, the horizontal rectangular coordinate axis. Optionally, one can then rotate the rectangular image by 90deg, then again sample onto the hexagonal grid and check for line segments at angles of 0deg, 60deg, and 120deg to the original horizontal coordinate axis. The net result is that one has checked for line segments at angular intervals of 30deg. For even finer angular resolution, one could, for example, then rotate the rectangular-grid image +/-45deg before sampling to perform checking for line segments at angular intervals of 15deg.

Johnson, Gordon G.↗

Image-to-Image Wildfire Detection via Quantum-Compatible Variational Segmentation from Remotely-sensed Data

Over the last decade, the incidence of wildfires has surged, causing widespread destruction globally. To better comprehend and manage these incidents, remote sensing and aerial missions have been implemented in recent efforts. However, this has resulted in an exponential rise in the amount of remote sensing data utilization, leading to a need for intelligent automation of data extraction in wildfire studies. Machine learning provides an accurate automated approach for detecting these natural anomalies and facilitates decision-makers to take prompt actions. To make insightful decisions in wildfire management, it is imperative to move beyond simple detection and explore the potential of probabilistic generative machine learning for creating "what-if" scenarios for various wildfire conditions. Such models offer improved representation of the stochastic nature of wildfire events. However, the optimization of these models can be computationally expensive, especially when using classical computers. Quantum computers have recently emerged as a promising solution to reduce the computational cost of training such models and improve their performance. In this study, we aim to utilize quantum-compatible machine learning techniques to implement our probabilistic generative approach. To that end, we propose a supervised probabilistic variational model consisting of a U-NET-based image-to-image component along with encoder and decoder networks which work as a variational autoencoder (VAE) component. Additionally, we explore the type of latent distribution type in the VAE component and implement different means for modeling the prior distribution. We further investigate the quantum-compatible versions of the model compared to the classical counterpart and benchmark potential benefits of quantum compatibility over the classical model.

quantum machine learning↗

Face-Sheet Quality Analysis and Thermo-Physical Property Characterization of OOA and Autoclave Panels

Increased application of polymer matrix composite (PMC) materials in large vehicle structures requires consideration of non-autoclave manufacturing technology. The NASA Composites for Exploration project, and its predecessor, Lightweight Spacecraft Structures and Materials project, were tasked with the development of materials and manufacturing processes for structures that will perform in a heavy-lift-launch vehicle environment. Both autoclave and out of autoclave processable materials were considered. Large PMC structures envisioned for such a vehicle included the payload shroud and the interstage connector. In this study, composite sandwich panels representing 1/16th segments of the barrel section of the Ares V rocket fairing were prepared as 1.8 m x 2.4 m sections of the 10 m diameter arc segment. IM7/977-3 was used as the face-sheet prepreg of the autoclave processed panels and T40-800B/5320-1 for the out of autoclave panels. The core was 49.7 kg/sq m (3.1 lb/cu ft (pcf)) aluminum honeycomb. Face-sheets were fabricated by automated tape laying 153 mm wide unidirectional tape. This work details analysis of the manufactured panels where face-sheet quality was characterized by optical microscopy, cured ply thickness measurements, acid digestion, and thermal analysis.

Miller, Sandi G.↗

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. Furthermore, an iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

36 MATERIALS SCIENCE↗

Predicting operator workload during system design

A workload prediction methodology was developed in response to the need to measure workloads associated with operation of advanced aircraft. The application of the methodology will involve: (1) conducting mission/task analyses of critical mission segments and assigning estimates of workload for the sensory, cognitive, and psychomotor workload components of each task identified; (2) developing computer-based workload prediction models using the task analysis data; and (3) exercising the computer models to produce predictions of crew workload under varying automation and/or crew configurations. Critical issues include reliability and validity of workload predictors and selection of appropriate criterion measures.

Aldrich, Theodore B.↗

Structures for remotely deployable precision antennas

Future space missions such as the Earth Science Geostationary Platform (ESGP) will require highly accurate antennas with apertures that cannot be launched fully formed. The operational orbits are often inaccessible to manned flight and will involve expendable launch vehicles such as the Delta or Titan. There is therefore a need for completely deployable antenna reflectors of large size capable of efficiently handling millimeter wave electromagnetic radiation. The parameters for the type of mission are illustrated. The logarithmic plot of frequency versus aperture diameter shows the regions of interest for a large variety of space antenna applications, ranging from a 1500-meter-diameter radio telescope for low frequencies to a 20-meter-diameter infrared telescope. For the ESGP, a major application is the microwave radiometry at high frequencies for atmospheric sounding. Almost all existing large antenna reflectors for space employ a mesh-type reflecting surface. Examples are shown and discussed which deal with the various structural concepts for mesh antennas. Fortunately, those concepts are appropriate for creating the very large apertures required at the lower frequencies for good resolution. The emphasis is on the structural concepts and technologies that are appropriate to fully automated deployment of dish-type antennas with solid reflector surfaces. First the structural requirements are discussed. Existing concepts for fully deployable antennas are then described and assessed relative to the requirements. Finally, several analyses are presented that evaluate the effects of beam steering and segmented reflector design on the accuracy of the antenna.

Hedgepeth, J. M.↗

Object Recognition using Feature- and Color-Based Methods

An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

Duong, Tuan↗

Regional technology transfer program

The continuing operation is reported of a jointly state- and NASA-sponsored Regional Dissemination Center serving the southeastern United States. The NC/STRC offers automated searching of large information collections, such as that assembled by NASA, with emphasis on textile-related files to serve regional industry. During this period, NC/STRC conducted an in-depth analysis of its marketing programs and prepared a series of brochures aimed at various segments of industry. Heavy emphasis was also placed on the Library Search Service inaugurated by NC/STRC, and a total of 32 universities now participate in this service. Smaller schools are served through the university network. Although the nationwide industrial recession caused a general drop in search requests, NC/STRC processed a total of 838 retrospective searches during this period: 39.97% for its industrial clients, 22.9% for university libraries, and 37.1% for other RDC's.

Source record↗

Expansion of epicyclic gear dynamic analysis program

The multiple mesh/single stage dynamics program is a gear tooth analysis program which determines detailed geometry, dynamic loads, stresses, and surface damage factors. The program can analyze a variety of both epicyclic and single mesh systems with spur or helical gear teeth including internal, external, and buttress tooth forms. The modifications refine the options for the flexible carrier and flexible ring gear rim and adds three options: a floating Sun gear option; a natural frequency option; and a finite element compliance formulation for helical gear teeth. The option for a floating Sun incorporates two additional degrees of freedom at the Sun center. The natural frequency option evaluates the frequencies of planetary, star, or differential systems as well as the effect of additional springs at the Sun center and those due to a flexible carrier and/or ring gear rim. The helical tooth pair finite element calculated compliance is obtained from an automated element breakup of the helical teeth and then is used with the basic gear dynamic solution and stress postprocessing routines. The flexible carrier or ring gear rim option for planetary and star spur gear systems allows the output torque per carrier and ring gear rim segment to vary based on the dynamic response of the entire system, while the total output torque remains constant.

Boyd, Linda Smith↗