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At least 1,171 records · Page 65

In-Situ Characterization of Pore Formation Dynamics in Pulsed Wave Laser Powder Bed Fusion

Laser powder bed fusion (LPBF) is an additive manufacturing technology with the capability of printing complex metal parts directly from digital models. Between two available emission modes employed in LPBF printing systems, pulsed wave (PW) emission provides more control over the heat input compared to continuous wave (CW) emission, which is highly beneficial for printing parts with intricate features. However, parts printed with pulsed wave LPBF (PW-LPBF) commonly contain pores, which degrade their mechanical properties. In this study, we reveal pore formation mechanisms during PW-LPBF in real time by using an in-situ high-speed synchrotron x-ray imaging technique. We found that vapor depression collapse proceeds when the laser irradiation stops within one pulse, resulting in occasional pore formation during PW-LPBF. We also revealed that the melt ejection and rapid melt pool solidification during pulsed-wave laser melting resulted in cavity formation and subsequent formation of a pore pattern in the melted track. The pore formation dynamics revealed here may provide guidance on developing pore elimination approaches.

36 MATERIALS SCIENCE↗

Magnetic Tape Recording for the Eighties

The practical and theoretical aspects of state-of-the-art magnetic tape recording technology are reviewed. Topics covered include the following: (1) analog and digital magnetic tape recording, (2) tape and head wear, (3) wear testing, (4) magnetic tape certification, (5) care, handling, and management of magnetic tape, (6) cleaning, packing, and winding of magnetic tape, (7) tape reels, bands, and packaging, (8) coding techniques for high-density digital recording, and (9) tradeoffs of coding techniques.

Kalil, Ford↗

Super magnets for large tunnels

The development and use of a large Magnetic Suspension and Balance System (MSBS) in wind tunnels is examined, discussing NASA-sponsored research to develop a large MSBS, and the 2 MSBS already in use. The MSBS holds the model in an arbitrary position in the wind tunnel test section and measures the forces and moments acting on the model. Technologies for building a large MSBS have been developed, and research is being done to reduce building costs. Magnetic suspension is advantageous because it completely eliminates interference from mechanical support systems such as stings or struts and it allows for easy rotation and translation of the model. Advances allowing operation at higher temperatures, probably using liquid nitrogen instead of liquid helium may reduce the cost of MSBS operation. A large MSBS would require power controllers with capacity up to 10 MW, efficiency approaching 98 percent and the ability to reverse the sign of both voltage and current. Technologies include the electro-magnetic position sensor, model positioning sensing, digital controller, and a precalibrated resistance strain-gage balance.

Boyden, Richmond P.↗

Aeroservoelastic wind-tunnel investigations using the Active Flexible Wing Model: Status and recent accomplishments

The status of the joint NASA/Rockwell Active Flexible Wing Wind-Tunnel Test Program is described. The objectives are to develop and validate the analysis, design, and test methodologies required to apply multifunction active control technology for improving aircraft performance and stability. Major tasks include designing digital multi-input/multi-output flutter-suppression and rolling-maneuver-load alleviation concepts for a flexible full-span wind-tunnel model, obtaining an experimental data base for the basic model and each control concept and providing comparisons between experimental and analytical results to validate the methodologies. The opportunity is provided to improve real-time simulation techniques and to gain practical experience with digital control law implementation procedures.

Noll, Thomas E.↗

Space Transportation Avionics Technology Symposium. Volume 1: Executive summary

The focus of the symposium was to examine existing and planned avionics technology processes and products and to recommend necessary changes for strengthening priorities and program emphases. Innovative changes in avionics technology development and design processes, identified during the symposium, are needed to support the increasingly complex, multi-vehicle, integrated, autonomous space-based systems. Key technology advances make such a major initiative viable at this time: digital processing capabilities, integrated on-board test/checkout methods, easily reconfigurable laboratories, and software design and production techniques.

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Exploration of operator method digital optical computers for application to NASA

Digital optical computer design has been focused primarily towards parallel (single point-to-point interconnection) implementation. This architecture is compared to currently developing VHSIC systems. Using demonstrated multichannel acousto-optic devices, a figure of merit can be formulated. The focus is on a figure of merit termed Gate Interconnect Bandwidth Product (GIBP). Conventional parallel optical digital computer architecture demonstrates only marginal competitiveness at best when compared to projected semiconductor implements. Global, analog global, quasi-digital, and full digital interconnects are briefly examined as alternative to parallel digital computer architecture. Digital optical computing is becoming a very tough competitor to semiconductor technology since it can support a very high degree of three dimensional interconnect density and high degrees of Fan-In without capacitive loading effects at very low power consumption levels.

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Space Transportation Avionics Technology Symposium. Volume 2: Conference Proceedings

The focus of the symposium was to examine existing and planned avionics technology processes and products and to recommend necessary changes for strengthening priorities and program emphases. Innovative changes in avionics technology development and design processes are needed to support the increasingly complex, multi-vehicle, integrated, autonomous space-based systems. Key technology advances make such a major initiative viable at this time: digital processing capabilities, integrated on-board test/checkout methods, easily reconfigurable laboratories, and software design and production techniques.

Source record↗

Support of Helicopter 'Free Flight' Operations in the 1996 Olympics

The microcosm of activity surrounding the 1996 Olympic Games provided researchers an opportunity for demonstrating state-of-the art technology in the first large-scale deployment of a prototype digital communication/navigation/surveillance system in a confined environment. At the same time it provided an ideal opportunity for transportation officials to showcase the merits of an integrated transportation system in meeting the operational needs to transport time sensitive goods and provide public safety services under real-world conditions. Five aeronautical CNS functions using a digital datalink system were chosen for operational flight testing onboard 91 aircraft, most of them helicopters, participating in the Atlanta Short-Haul Transportation System. These included: GPS-based Automatic Dependent Surveillance, Cockpit Display of Traffic Information, Controller-Pilot Communications, Graphical Weather Information (uplink), and Automated Electronic Pilot Reporting (downlink). Atlanta provided the first opportunity to demonstrate, in an actual operating environment, key datalink functions which would enhance flight safety and situational awareness for the pilot and supplement conventional air traffic control. The knowledge gained from such a large-scale deployment will help system designers in development of a national infrastructure where aircraft would have the ability to navigate autonomously.

Branstetter, James R.↗

Geographic Information System Data Analysis

Data was collected in order to further NASA Langley Research Center's Geographic Information System(GIS). Information on LaRC's communication, electrical, and facility configurations was collected. Existing data was corrected through verification, resulting in more accurate databases. In addition, Global Positioning System(GPS) points were used in order to accurately impose buildings on digitized images. Overall, this project will help the Imaging and CADD Technology Team (ICTT) prove GIS to be a valuable resource for LaRC.

Billings, Chad↗

Optical Channelizer Evaluation Using Empirical Data and Simulation

Westinghouse Electric Corporation Division under NASA contract NAS3-25865 developed a proof-of-concept (POC) multichannel demultiplexer implemented as an acousto-optic radiofrequency (RF) with a spectrum analyzer. A detailed analysis of the experimental results indicate that the expected degradation caused by the acousto-optical channelizer is approximately 2.0 dB degradation at 10(exp -5) bit-error rate (BER) and 3.0 dB degradation at 10(exp -8) BER. This degradation may be quite acceptable when considering the excellent volume, mass, and power characteristics of acousto-optical channelizing relative to other technologies. In addition, system performance can be greatly improved by using digital pulse shaping in the modem and increasing the channel spacing from 40 to 45 kHz for 64 kbps quadrature phase-shift keying (QPSK) modulation.

Ivancic,William D.↗

Design and Specification of Optical Bandpass Filters for Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS)

Advanced optical bandpass filters for the Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS) have been developed on a filter-by-filter basis through detailed studies which take into account the instrument's science goals, available optical filter fabrication technology, and developments in ACS's charge-coupled-device (CCD) detector technology. These filters include a subset of filters for the Sloan Digital Sky Survey (SDSS) which are optimized for astronomical photometry using today's charge-coupled-devices (CCD's). In order for ACS to be truly advanced, these filters must push the state-of-the-art in performance in a number of key areas at the same time. Important requirements for these filters include outstanding transmitted wavefront, high transmittance, uniform transmittance across each filter, spectrally structure-free bandpasses, exceptionally high out of band rejection, a high degree of parfocality, and immunity to environmental degradation. These constitute a very stringent set of requirements indeed, especially for filters which are up to 90 mm in diameter. The highly successful paradigm in which final specifications for flight filters were derived through interaction amongst the ACS Science Team, the instrument designer, the lead optical engineer, and the filter designer and vendor is described. Examples of iterative design trade studies carried out in the context of science needs and budgetary and schedule constraints are presented. An overview of the final design specifications for the ACS bandpass and ramp filters is also presented.

Leviton, Douglas B.↗

Digital Imaging

Digital Imaging is the computer processed numerical representation of physical images. Enhancement of images results in easier interpretation. Quantitative digital image analysis by Perceptive Scientific Instruments, locates objects within an image and measures them to extract quantitative information. Applications are CAT scanners, radiography, microscopy in medicine as well as various industrial and manufacturing uses. The PSICOM 327 performs all digital image analysis functions. It is based on Jet Propulsion Laboratory technology, is accurate and cost efficient.

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Superconducting Digital Multiplexers for Sensor Arrays

Arrays of cryogenic microbolometers and other cryogenic detectors are being developed for infrared imaging. If the signal from each sensor is amplified, multiplexed, and digitized using superconducting electronics, then this data can be efficiently read out to ambient temperature with a minimum of noise and thermal load. HYPRES is developing an integrated system based on SQUID amplifiers, a high-resolution analog-to-digital converter (ADC) based on RSFQ (rapid single flux quantum) logic, and a clocked RSFQ multiplexer. The ADC and SQUIDs have already been demonstrated for other projects, so this paper will focus on new results of a digital multiplexer. Several test circuits have been fabricated using Nb Josephson technology and are about to be tested at T = 4.2 K, with a more complete prototype in preparation.

Kadin, Alan M.↗

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems.

context-sensitive↗

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools II: Contextual Constraints and Information Sources

Recent advances in artificial intelligence, machine learning, data mining and sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the second of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explored fundamental issues associated with the development of such a system. In this report, we extend this work to focus on two critical aspects of these systems: 1) the constraints and conditions that drive the dynamic prioritization and presentation of data and information to the pilots, and 2) specific data and information to be accessed, monitored, integrated, and displayed in such a system.

context-sensitive↗

Natural Language Processing Analysis of Notices to Airmen for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized.

Natural Language Processing↗

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized. Video is an mp4 download, with a play time of 9 min 35 secs.

Natural Language Processing↗

Detection of Anomalous Events in Electronic Health Records

Over the past decade, Health Information Technology (Health IT) has enabled an explosion in the amount of digital information stored in electronic health records (EHRs). According to recent studies, safety-related issues in healthcare can present themselves as anomalies in EHR data. Motivating examples of anomalous events in EHRs include clinical events related to invalid order cancellations or rejections, which may be initiated by clinical staff or automatic software routines in Health IT systems. Such events may be detected using anomaly detection or change point detection methods. In this paper, we explore the use of a forecasting approach to detect anomalies in EHR data using an online Support Vector Regression technique. Specifically, the proposed approach uses temporal frequency of activities in EHRs, coupled with dynamic robust confidence intervals, to characterize events as normal or anomalous. Once an event is characterized as an anomaly, our approach suppresses its effects in subsequent time intervals. The proposed approach shows encouraging results using real-world EHR data from the Veterans Affairs' corporate data warehouse

Pellett, Jordan J.↗