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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Field Results from Three Campaigns to Validate the Performance of the Miniaturized Laser Heterodyne Radiometer (Mini‐LHR) for Measuring Carbon Dioxide and Methane in the Atmospheric Column

In a collaboration between NASA GSFC and GWU, a low-cost, surface instrument is being developed that can continuously monitor key carbon cycle gases in the atmospheric column: carbon dioxide (CO2) and methane (CH4). The instrument is based on a miniaturized, laser heterodyne radiometer (LHR) using near infrared (NIR) telecom lasers. Despite relatively weak absorption line strengths in this spectral region, spectrallyresolved atmospheric column absorptions for these two molecules fall in the range of 60-80% and thus sensitive and precise measurements of column concentrations are possible. In the last year, the instrument was deployed for field measurements at Park Falls, Wisconsin; Castle Airport near Atwater, California; and at the NOAA Mauna Loa Observatory in Hawaii. For each subsequent campaign, improvement in the figures of merit for the instrument has been observed. In the latest work the absorbance noise is approaching 0.002 optical density (OD) noise on a 1.8 OD signal. An overview of the measurement campaigns and the data retrieval algorithm for the calculation of column concentrations will be presented. For light transmission through the atmosphere, it is necessary to account for variation of pressure, temperature, composition, and refractive index through the atmosphere that are all functions of latitude, longitude, time of day, altitude, etc. For temperature, pressure, and humidity profiles with altitude we use the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data. Spectral simulation is accomplished by integrating short-path segments along the trajectory using the SpecSyn spectral simulation suite developed at GW. Column concentrations are extracted by minimizing residuals between observed and modeled spectrum using the Nelder-Mead simplex algorithm. We will also present an assessment of uncertainty in the reported concentrations from assumptions made in the meteorological data, LHR instrument and tracker noise, and radio frequency bandwidth and describe additional future goals in instrument development and deployment target

meteorological data↗
NASA NTRS2014

Acoustics Research of Propulsion Systems

The liftoff phase induces high acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests to generate 1/3 octave band Sound Pressure Level (SPL) spectra. In an effort to update the accuracy and quality of liftoff acoustic loading predictions, non-stationary flight data from the Ares I-X were processed in PC-Signal in two flight phases: simulated hold-down and liftoff. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semi-empirical methods. This consisted of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares I-X flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Gao, Ximing↗
NASA NTRS2015

A Review of Head-Worn Display Research at NASA Langley Research Center

NASA Langley has conducted research in the area of helmet-mounted/head-worn displays over the past 30 years. Initially, NASA Langley's research focused on military applications, but recently it has conducted a line of research in the area of head-worn displays for commercial and business aircraft. This work has revolved around numerous simulation experiments as well as flight tests to develop technology and data for industry and regulatory guidance. The paper summarizes the results of NASA's helmet-mounted/head-worn display research. Of note, the work tracks progress in wearable collimated optics, head tracking, latency reduction, and weight. The research lends credence that a small, sunglasses-type form factor of the head-worn display would be acceptable to commercial pilots, and this goal is now becoming technologically feasible. The research further suggests that a head-worn display may serve as an "equivalent" Head-Up Display (HUD) with safety, operational, and cost benefits. "HUD equivalence" appears to be the economic avenue by which head-worn displays can become main-stream on the commercial and business aircraft flight deck. If this happens, NASA's research suggests that additional operational benefits using the unique capabilities of the head-worn display can open up new operational paradigms.

Arthur, Jarvis (Trey) J., III↗
NASA NTRS2015

AST Launch Vehicle Acoustics

The liftoff phase induces acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are then used in the prediction of internal vibration responses of the vehicle and components which result in the qualification levels. Thus, predicting these liftoff acoustic (LOA) environments is critical to the design requirements of any launch vehicle. If there is a significant amount of uncertainty in the predictions or if acoustic mitigation options must be implemented, a subscale acoustic test is a feasible pre-launch test option to verify the LOA environments. The NASA Space Launch System (SLS) program initiated the Scale Model Acoustic Test (SMAT) to verify the predicted SLS LOA environments and to determine the acoustic reduction with an above deck water sound suppression system. The SMAT was conducted at Marshall Space Flight Center and the test article included a 5% scale SLS vehicle model, tower and Mobile Launcher. Acoustic and pressure data were measured by approximately 250 instruments. The SMAT liftoff acoustic results are presented, findings are discussed and a comparison is shown to the Ares I Scale Model Acoustic Test (ASMAT) results.

Houston, Janice↗
NASA NTRS2015

SLS Scale Model Acoustic Test Liftoff Results and Comparisons

The liftoff phase induces acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are then used in the prediction of internal vibration responses of the vehicle and components which result in the qualification levels. Thus, predicting these liftoff acoustic (LOA) environments is critical to the design requirements of any launch vehicle. If there is a significant amount of uncertainty in the predictions or if acoustic mitigation options must be implemented, a subscale acoustic test is a feasible design phase test option to verify the LOA environments. The NASA Space Launch System (SLS) program initiated the Scale Model Acoustic Test (SMAT) to verify the predicted SLS LOA environments.

Houston, Janice↗
NASA NTRS2016

Liftoff and Time Equivalent Duration Data Evaluation of Exploration Flight Test 1 Orion Multi-Purpose Crew Vehicle

The liftoff phase induces high acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. There arises the question about time equivalent (Teq) duration of the liftoff phase and similarity to other launch vehicles. Vibroacoustic engineers require the fatigue-weighted time duration values for qualification testing inputs. In order to determine the Teq for the Space Launch System, NASA's newest launch vehicle, the external microphone data from the Exploration Flight Test 1 (EFT-1) flight of the Orion Multi-Purpose Crew Vehicle (MPCV) was evaluated. During that evaluation, a trend was observed in the data and the origin of that trend is discussed in this paper. Finally, the Teq values for the EFT-1 Orion MPCV are presented.

Houston, Janice↗
NASA NTRS2017

Development of Increasingly Autonomous Traffic Data Manager Using Pilot Relevancy and Ranking Data

NASA's Safe Autonomous Systems Operations (SASO) project goal is to define and safely enable all future airspace operations by justifiable and optimal autonomy for advanced air, ground, and connected capabilities. This work showcases how Increasingly Autonomous Systems (IAS) could create operational transformations beneficial to the enhancement of civil aviation safety and efficiency. One such IAS under development is the Traffic Data Manager (TDM). This concept is a prototype 'intelligent party-line' system that would declutter and parse out non-relevant air traffic, displaying only relevant air traffic to the aircrew in a digital data communications (Data Comm) environment. As an initial step, over 22,000 data points were gathered from 31 Airline Transport Pilots to train the machine learning algorithms designed to mimic human experts and expertise. The test collection used an analog of the Navigation Display. Pilots were asked to rate the relevancy of the displayed traffic using an interactive tablet application. Pilots were also asked to rank the order of importance of the information given, to better weight the variables within the algorithm. They were also asked if the information given was enough data, and more importantly the "right" data to best inform the algorithm. The paper will describe the findings and their impact to the further development of the algorithm for TDM and, in general, address the issue of how can we train supervised machine learning algorithms, critical to increasingly autonomous systems, with the knowledge and expertise of expert human pilots.

Le Vie, Lisa R.↗
NASA NTRS2017

Autonomous System Technologies for Resilient Airspace Operations

Increasing autonomous systems within the aircraft cockpit begins with an effort to understand what autonomy is and developing the technology that encompasses it. Autonomy allows an agent, human or machine, to act independently within a circumscribed set of goals; delegating responsibility to the agent(s) to achieve overall system objective(s). Increasingly Autonomous Systems (IAS) are the highly sophisticated progression of current automated systems toward full autonomy. Working in concert with humans, these types of technologies are expected to improve the safety, reliability, costs, and operational efficiency of aviation. IAS implementation is imminent, which makes the development and the proper performance of such technologies, with respect to cockpit operation efficiency, the management of air traffic and data communication information, vital. A prototype IAS agent that attempts to optimize the identification and distribution of "relevant" air traffic data to be utilized by human crews during complex airspace operations has been developed.

Houston, Vincent E.↗
NASA NTRS2018

Imaging X-ray Polarimetry Explorer Mission Overview and Systems Engineering Status

The Imaging X-ray Polarimetry Explorer (IXPE) is a space-based observatory that will have the capability to measure the polarization of X-rays from astrophysical sources. IXPE will improve sensitivity over OSO-8, the only previous X-ray polarimeter, by two orders of magnitude in required exposure time. IXPE will yield insight into our understanding of X-ray production in objects such as neutron stars as well as stellar and supermassive black holes. IXPE measurements will provide new dimensions for probing a wide range of cosmic X-ray sources-including active galactic nuclei (AGN) and microquasars, pulsars and pulsar wind nebulae, magnetars, accreting X-ray binaries, supernova remnants, and the Galactic center.

Houston, Janice↗
NASA NTRS2018

Impact of Advanced Synoptics and Simplified Checklists During Aircraft Systems Failures

Abstract—Natural human capacities are becoming increasingly mismatched to the enormous data volumes, processing capabilities, and decision speeds demanded in today’s aviation environment. Increasingly Autonomous Systems (IAS) are uniquely suited to solve this problem. NASA is conducting research and development of IAS - hardware and software systems, utilizing machine learning algorithms, seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. IAS offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. A human-in-the-loop test was conducted in NASA Langley’s Integration Flight Deck B-737-800 simulator to evaluate advanced synoptic pages with simplified interactive electronic checklists as an IAS for routine air carrier flight operations and in response to aircraft system failures. Twelve U.S. airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to failures. These data are fundamental to and critical for the design and development of future increasingly autonomous systems that can better support the human in the cockpit. Synoptic pages and electronic checklists significantly improved pilot responses to non-normal scenarios, but implementation of these aids and other intelligent assistants have barriers to implementation (e.g., certification cost) that must overcome.

Etherington, Timothy J.↗
NASA NTRS2019

Advancing Aircraft Operations in a Net-Centric Environment with the Incorporation of Increasingly Autonomous Systems and Human Teaming

NextGen has begun the modernization of the nation’s air transportation system, with goals to improve system safety, increase operation efficiency and capacity, provide enhanced predictability, resilience and robustness. With these improvements, NextGen is poised to handle significant increases in air traffic operations, more than twice the number recorded in 2016, by 2025.1 NextGen is evolving toward collaborative decision-making across many agents, including automation, by use of a Net-Centric architecture, which in itself creates a very complex environment in which the navigation and operation of aircraft are to take place. An intricate environment such as this, coupled with the expected upsurge of air traffic operations generates concern respecting the ability of the human-agent to both fly and manage aircraft within. Therefore, it is both necessary and practical to begin the process of increasingly autonomous systems within the cockpit that will act independently to assist the human-agent achieve the overall goal of NextGen. However, the straightforward technological development and implementation of intelligent machines into the cockpit is only part of what is necessary to maintain, at minimum, or improve human-agent functionality, as desired, while operating in NextGen. The full integration of Increasingly Autonomous Systems (IAS) within the cockpit can only be accomplished when the IAS works in concert with the human, formulating trust between the two, thereby establishing a team atmosphere. Imperative to cockpit implementation is ensuring the proper performance of the IAS by the development team and the human-agent with which it will be paired when given a specific piloting, navigation, or observational task. Described in this paper are the steps taken, at NASA Langley Research Center, during the second and third phases of the development of an IAS, the Traffic Data Manager (TDM), its verification and validation by human-agents, and the foundational development of Human Autonomy Teaming (HAT) between the two.

Houston, Vincent E.↗
NASA NTRS2019

Evaluation of Technology Concepts for Traffic Data Management and Relevant Audio for Datalink in Commercial Airline Flight Decks

Datalink is currently operational for departure clearances and in oceanic environments and is currently being tested in high altitude domestic enroute airspace. Interaction with even simple datalink clearances may create more workload for flight crews than the voice system they replace if not carefully designed. Datalink may also introduce additional complexity for flight crews with hundreds of uplink messages now defined for use. Finally, flight crews may lose airspace awareness and operationally relevant information that they normally pickup from Air Traffic Control (ATC) voice communications with other aircraft (i.e., “party-line” transmissions). Once again, automation may be poised to increase workload on the flight deck for incremental benefit. Datalink implementation to support future air traffic management concepts needs to be carefully considered, understanding human communication norms and especially, the change from voice- to text-based communications modality and its effect on pilot workload and situation awareness. Increasingly autonomous systems, where autonomy is designed to support human-autonomy teaming, may be suited to solve these issues. NASA is conducting research and development of increasingly autonomous systems, utilizing machine-learning algorithms seamlessly integrated with humans whereby task performance of the combined system is significantly greater than the individual components. Increasingly autonomous systems offer the potential for significantly improved levels of performance and safety that are superior to either human or automation alone. Two increasingly autonomous systems concepts - a traffic data manager and a conversational co-pilot - were developed to intelligently address the datalink issues in a complex, future state environment with significant levels of traffic. The system was tested for suitability of datalink usage for terminal airspace. The traffic data manager allowed for automated declutter of the Automatic Dependent Surveillance-Broadcast (ADS-B) display. The system determined relevant traffic for display based on machine learning algorithms trained by experienced human pilot behaviors. The conversational co-pilot provided relevant audio air traffic control messages based on context and proximity to ownship. Both systems made use of the connected aircraft concepts to provide intelligent context to determine relevancy above and beyond proximity to ownship. A human-in-the-loop test was conducted in NASA Langley Research Center’s Integration Flight Deck B-737-800 simulator to evaluate the traffic data manager and the conversational co-pilot. Twelve airline crews flew various normal and non-normal procedures and their actions and performance were recorded in response to the procedural events. This paper details the flight crew performance and evaluation during the events.

Etherington, Timothy↗
NASA NTRSDate not supplied

TPSAS-NF1676L-12439-DND

Goal: Increase aircraft throughput at the runway threshold by controlling the spacing between aircraft to a greater precision than can be accomplished today. APS is a time-based spacing concept, today’s system relies on distance-based spacing. ATC determines a spacing interval between a leading and trailing aircraft, then issues a clearance to the trailing aircraft with that interval. The trailing aircraft performs speed changes during its approach to achieve its assigned time spacing with respect to the leading aircraft at the runway threshold. The first in a chain of aircraft does not have a leading aircraft and is assigned a required time of arrival (RTA) at the runway threshold.

Frederick Wieland↗
NASA NTRSDate not supplied

TPSAS-NF1676L-31816-DND

A net-centric air space system or architecture is a continuously evolving environment in which people, devices, information, and services are interconnected via a communications network. Inherent in this type of domain is an overwhelming amount of various forms of data that can provide decision makers, pilots, and air traffic controllers with superior awareness concerning events and conditions within it. Assisting a flight crew in gathering, organizing, and disseminating these data expeditiously is imperative and calls for implementation of technologies such as Increasingly Autonomous Systems designed to support future flight operations conducted within a net-centric national air space system.

Vincent E Houston↗