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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Reliability Analysis for AFTI-F16 SRFCS Using ASSIST and SURE

This paper reports the results of a study on reliability analysis of an AFTI-16 Self-Repairing Flight Control System (SRFCS) using software tools SURE (Semi-Markov Unreliability Range Evaluator and ASSIST (Abstract Semi-Markov Specification Interface to the SURE Tool). The purpose of the study is to investigate the potential utility of the software tools in the ongoing effort of the NASA Aviation Safety Program, where the class of systems must be extended beyond the originally intended serving class of electronic digital processors. The study concludes that SURE and ASSIST are applicable to reliability, analysis of flight control systems. They are especially efficient for sensitivity analysis that quantifies the dependence of system reliability on model parameters. The study also confirms an earlier finding on the dominant role of a parameter called a failure coverage. The paper will remark on issues related to the improvement of coverage and the optimization of redundancy level.

Wu, N. Eva↗
NASA NTRS2019

The Role of Alerting System Failures in Loss of Control Accidents CAST SE-210 Output 2

This report is part of a series of reports that address flight deck design and evaluation, written as a response to loss of control accidents. In particular, this activity is directed at failures in airplane state awareness in which the pilot loses awareness of the airplane's energy state or attitude and enters an upset condition. In a report by the Commercial Aviation Safety Team, an analysis of accidents and incidents related to loss of airplane state awareness determined that hazard alerting was not effective in producing the appropriate pilot response to a hazard (CAST, 2014). In the current report, we take a detailed look at 28 airplane state awareness accidents and incidents to determine how well the hazard alerting worked. We describe a five-step integrated alerting-to-recovery sequence that prescribes how hazard alerting should lead to effective flight crew actions for managing the hazard. Then, for each hazard in each of the 28 events, we determine if that sequence failed and, if so, how it failed. The results show that there was an alerting failure in every one of the 28 safety events, and that the most frequent failure (20/28) was tied to the flight crew not orienting to (not being aware of) the hazard. The discussion section summarizes findings and identifies alerting issues that are being addressed and issues that are not currently being addressed. We identify a few recent upgrades that have addressed certain alerting failures. Two of these upgrades address alerting design, but one response to the safety events is to upgrade training for approach to stall and stall recovery. We also describe issues that are not being addressed adequately: better alert integration for flight path management types of hazards, airplanes in the fleet that do not meet the current alerting regulations, a lack of innovation for addressing cases of channelized attention, and existing vulnerabilities in managing data validity.

aviation safety↗
DOE OSTI2024

Sustainable Aviation Fuel Blending and Logistics

Worldwide, aviation accounts for 2% of all manmade carbon dioxide emissions and 12% of all transportation CO2 emissions. In 2023, the U.S. accounted for 27% of the world jet fuel consumption. The aviation industry has set sustainability goals, and mandates. Sustainable aviation fuel (SAF), made from nonpetroleum feedstocks, significantly reduces aviation emissions. SAF must be blended with petroleum-based jet fuel prior to its use in aircraft. Jet fuel quality standards and certification documents are essential to fuel performance, operability, and safety and are the primary driver in determining locations for blending. Several locations were evaluated including terminals, airports, refineries, and greenfield/brownfield sites. While all the locations evaluated are technically capable of blending fuel, there are practical considerations that make terminals the optimal location for blending. The report includes background on jet fuel and SAF use, fuel quality standards, modes of transport for both conventional jet fuel and SAF, and terminal information.

09 BIOMASS FUELS↗
NASA NTRS2001

Integrating Safety in the Aviation System: Interdepartmental Training for Pilots and Maintenance Technicians

The study of human factors has had a decisive impact on the aviation industry. However, the entire aviation system often is not considered in researching, training, and evaluating human factors issues especially with regard to safety. In both conceptual and practical terms, we argue for the proactive management of human error from both an individual and organizational systems perspective. The results of a multidisciplinary research project incorporating survey data from professional pilots and maintenance technicians and an exploratory study integrating students from relevant disciplines are reported. Survey findings suggest that latent safety errors may occur during the maintenance discrepancy reporting process because pilots and maintenance technicians do not effectively interact with one another. The importance of interdepartmental or cross-disciplinary training for decreasing these errors and increasing safety is discussed as a primary implication.

Mattson, Marifran↗
NASA NTRS2001

Preliminary Results Obtained in Integrated Safety Analysis of NASA Aviation Safety Program Technologies

This is a listing of recent unclassified RTO technical publications processed by the NASA Center for AeroSpace Information from January 1, 2001 through March 31, 2001 available on the NASA Aeronautics and Space Database. Contents include 1) Cognitive Task Analysis; 2) RTO Educational Notes; 3) The Capability of Virtual Reality to Meet Military Requirements; 4) Aging Engines, Avionics, Subsystems and Helicopters; 5) RTO Meeting Proceedings; 6) RTO Technical Reports; 7) Low Grazing Angle Clutter...; 8) Verification and Validation Data for Computational Unsteady Aerodynamics; 9) Space Observation Technology; 10) The Human Factor in System Reliability...; 11) Flight Control Design...; 12) Commercial Off-the-Shelf Products in Defense Applications.

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NASA NTRS2016

Flight Test Assessments of Pilot Workload, System Usability, and Situation Awareness of TASAR

Traffic Aware Strategic Aircrew Requests (TASAR) is an onboard automation concept intended to identify trajectory optimizations, in terms of fuel and time saving objectives, clear of known traffic, weather, and airspace restrictions prior to the aircrew initiating a route-change request to Air Traffic Control (ATC). The software implementation of the TASAR concept is the Traffic Aware Planner (TAP). TASAR analysis and development is being executed by the NASA Langley Research Center's Crew Systems and Aviation Operations Branch (CSAOB) under the sponsorship of the Airspace Technology Demonstration (ATD) Project of the NASA Airspace Operations and Safety Program (AOSP). The TASAR Flight Trial-2 (FT-2) was conducted in June, 2015 out of the Newport News/Williamsburg International Airport. This flight trial was conducted using a Piaggio Avanti flight test aircraft and consisted of 12 Evaluation Flights with airline commercial pilots participating as the Evaluation Pilots, three destination airports in Atlanta and Jacksonville Air Route Traffic Control Centers, and one pair of flight plans associated with each destination airport. The primary goal of FT-2 was to reduce risk for upcoming operational trials with NASA partner airlines, Alaska Airlines and Virgin America. To accomplish this primary goal, six independent objectives were conducted during FT-2, however, this paper will report only the findings of Objective 5; the assessment of system usability, pilot perceived workload, and the degree of pilot acceptability of the TAP Human Machine Interface (HMI) during flight operations, via the administration of several subjective measures.

TASAR↗
NASA NTRS1987

Full-scale Transport Controlled Impact Demonstration Program

The Federal Aviation Administration (FAA) and NASA conducted a full-scale air-to-surface impact-survivable impact demonstration with a remotely piloted transport aircraft on 1 December 1984, at Edwards Air Force Base, California. The test article consisted of experiments, special equipment, and supporting systems, such as antimisting kerosene (AMK), crashworthiness structural/restraint, analytical modeling, cabin fire safety, flight data recorders, post-impact investigation, instrumentation/data acquisition systems, remotely piloted vehicle/flight control systems, range and flight safety provisions, etc. This report describes the aircraft, experiments, systems, activities, and events which lead up to the Controlled Impact Demonstration (CID). An overview of the final unmanned remote control flight and sequence of impact events are delineated. Preliminary post CID observations are presented.

Source record↗
NASA NTRS1999

The Typical General Aviation Aircraft

The reliability of General Aviation aircraft is unknown. In order to "assist the development of future GA reliability and safety requirements", a reliability study needs to be performed. Before any studies on General Aviation aircraft reliability begins, a definition of a typical aircraft that encompasses most of the general aviation characteristics needs to be defined. In this report, not only is the typical general aviation aircraft defined for the purpose of the follow-on reliability study, but it is also separated, or "sifted" into several different categories where individual analysis can be performed on the reasonably independent systems. In this study, the typical General Aviation aircraft is a four-place, single engine piston, all aluminum fixed-wing certified aircraft with a fixed tricycle landing gear and a cable operated flight control system. The system breakdown of a GA aircraft "sifts" the aircraft systems and components into five categories: Powerplant, Airframe, Aircraft Control Systems, Cockpit Instrumentation Systems, and the Electrical Systems. This breakdown was performed along the lines of a failure of the system. Any component that caused a system to fail was considered a part of that system.

Turnbull, Andrew↗
NASA NTRS1984

The Joint Airport Weather Studies Project - Current analysis highlights in the aviation safety context

The principal objective of the Joint Airport Weather Studies Project was to obtain high-resolution velocity, turbulence, and thermodynamic data on a convective outflow called a microburst, an intense downdraft and resulting horizontal outflow near the surface. Data collection occurred during the summer of 1982 near Denver, CO. Data sensors included three pulsed-microwave Doppler and two pulsed CO2 lidar radars, along with 27 Portable Automated Mesonet surface weather stations, the FAA's low-level-wind-shear alert system (LLWSAS), and five instrumented research aircraft. Convective storms occurred on 75 of 91 operational days, with Doppler data being collected on at least 70 microbursts. Analyses reported included a thorough examination of microburst-climatology statistics, the capability of the LLWSAS to detect adequately and accurately the presence of low-altitude wind shear danger to aircraft, the capability of a terminal Doppler radar system development to provide improved wind-shear detection and warning, and progress toward improved wind-shear training for pilots.

Mccarthy, J.↗
NASA NTRS1987

Wind Shear/Turbulence Inputs to Flight Simulation and Systems Certification

The purpose of the workshop was to provide a forum for industry, universities, and government to assess current status and likely future requirements for application of flight simulators to aviation safety concerns and system certification issues associated with wind shear and atmospheric turbulence. Research findings presented included characterization of wind shear and turbulence hazards based on modeling efforts and quantitative results obtained from field measurement programs. Future research thrusts needed to maximally exploit flight simulators for aviation safety application involving wind shear and turbulence were identified. The conference contained sessions on: Existing wind shear data and simulator implementation initiatives; Invited papers regarding wind shear and turbulence simulation requirements; and Committee working session reports.

Bowles, Roland L.↗
NASA NTRS1995

Weather Information System

WxLink is an aviation weather system based on advanced airborne sensors, precise positioning available from the satellite-based Global Positioning System, cockpit graphics and a low-cost datalink. It is a two-way system that uplinks weather information to the aircraft and downlinks automatic pilot reports of weather conditions aloft. Manufactured by ARNAV Systems, Inc., the original technology came from Langley Research Center's cockpit weather information system, CWIN (Cockpit Weather INformation). The system creates radar maps of storms, lightning and reports of surface observations, offering improved safety, better weather monitoring and substantial fuel savings.

Source record↗
NASA NTRS2006

Weather Information Communication (WINCOMM) VDL-3 and 1090ES Final Test Requirements, Test Plans, and Test Results

NASA s Aviation Safety Program was created for the purpose of making a significant reduction in the incidents of weather related aviation accidents by improving situational awareness. The objectives of that program are being met in part through advances in weather sensor technology, and in part through advances in the communications technology that are developed for use in the National Airspace System. It is this latter element, i.e., the improvements in aviation communication technologies, that is the focus of the Weather Information Communications project. This report describes the final flight test results completed under the WINCOMM project at the NASA Glenn Research Center of the 1090 Extended Squitter (1090ES) and VDL Mode 3 (VDL-3) data links as a medium for weather data exchange. It presents the use of 1090ES to meet the program objectives of sending broadcast turbulence information and the use of VDL-3 to send graphical weather images. This report provides the test requirements and test plans, which led to flight tests, as well as final results from flight testing. The reports define the changes made to both avionics and ground-based receivers as well as the ground infrastructure to support implementation of the recommended architecture, with a focus on the issues associated with these changes.

Griner, James H.↗
NASA NTRS2013

Evidence Report: Risk of Inadequate Human-Computer Interaction

Human-computer interaction (HCI) encompasses all the methods by which humans and computer-based systems communicate, share information, and accomplish tasks. When HCI is poorly designed, crews have difficulty entering, navigating, accessing, and understanding information. HCI has rarely been studied in an operational spaceflight context, and detailed performance data that would support evaluation of HCI have not been collected; thus, we draw much of our evidence from post-spaceflight crew comments, and from other safety-critical domains like ground-based power plants, and aviation. Additionally, there is a concern that any potential or real issues to date may have been masked by the fact that crews have near constant access to ground controllers, who monitor for errors, correct mistakes, and provide additional information needed to complete tasks. We do not know what types of HCI issues might arise without this "safety net". Exploration missions will test this concern, as crews may be operating autonomously due to communication delays and blackouts. Crew survival will be heavily dependent on available electronic information for just-in-time training, procedure execution, and vehicle or system maintenance; hence, the criticality of the Risk of Inadequate HCI. Future work must focus on identifying the most important contributing risk factors, evaluating their contribution to the overall risk, and developing appropriate mitigations. The Risk of Inadequate HCI includes eight core contributing factors based on the Human Factors Analysis and Classification System (HFACS): (1) Requirements, policies, and design processes, (2) Information resources and support, (3) Allocation of attention, (4) Cognitive overload, (5) Environmentally induced perceptual changes, (6) Misperception and misinterpretation of displayed information, (7) Spatial disorientation, and (8) Displays and controls.

Kritina Holden↗
NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events, and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, enable detection of atmospheric features during daytime operations with a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗
NASA NTRS2021

Aerosol and Cloud Detection Using Machine Learning Algorithms and Space-Based Lidar Data

Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, (1) increased the 1064 nm SNR by 75%, (2) increased the number of layers detected (any resolution) by 30%, and (3) enabled detection of 40% more atmospheric features during daytime operations at a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS operational data products. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.

lidar↗
NASA NTRS1996

Aeronautics and Space Report of the President: Fiscal Year 1996 Activities

Topics considered include: (1) Space launch activities: space shuttle missions; expendable launch vehicles. (2) Space science: astronomy and space physics; solar system exploration. (3) Space flight and technology: life and microgravity sciences; space shuttle technology; reuseable launch vehicles; international space station; energy; safety and mission assurance; commercial development and regulation of space; surveillance. (4) Space communications: communications satellites; space network; ground networks; mission control and data systems. (5) Aeronautical activities: technology developments; air traffic control and navigation; weather-related aeronautical activities; flight safety and security; aviation medicine and human factors. (6) Studies of the planet earth: terrestrial studies and applications: atmospheric studies: oceanographic studies; international aeronautical and space activities; and appendices.

Source record↗
NASA NTRS1997

Ring Buffered Network Bus

This report describes the research effort to demonstrate the integration of a data sharing technology, Ring Buffered Network Bus, in development by Dryden Flight Research Center, with an engine simulation application, the Java Gas Turbine Simulator, in development at the University of Toledo under a grant from the Glenn Research Center. The objective of this task was to examine the application of the RBNB technologies as a key component in the data sharing, health monitoring and system wide modeling elements of the NASA Aviation Safety Program (AVSP) [Golding, 1997]. System-wide monitoring and modeling of aircraft and air safety systems will require access to all data sources which are relative factors when monitoring or modeling the national airspace such as radar, weather, aircraft performance, engine performance, schedule and planning, airport configuration, flight operations, etc. The data sharing portion of the overall AVSP program is responsible for providing the hardware and software architecture to access and distribute data, including real-time flight operations data, among all of the AVSP elements. The integration of an engine code capable of numerically "flying" through recorded flight paths and weather data using a software tool that allows for distributed access of data to this engine code demonstrates initial steps toward building a system capable of monitoring and modeling the National Airspace.

Source record↗
NASA NTRS2002

Runway Safety Monitor Algorithm for Runway Incursion Detection and Alerting

The Runway Safety Monitor (RSM) is an algorithm for runway incursion detection and alerting that was developed in support of NASA's Runway Incursion Prevention System (RIPS) research conducted under the NASA Aviation Safety Program's Synthetic Vision System element. The RSM algorithm provides pilots with enhanced situational awareness and warnings of runway incursions in sufficient time to take evasive action and avoid accidents during landings, takeoffs, or taxiing on the runway. The RSM currently runs as a component of the NASA Integrated Display System, an experimental avionics software system for terminal area and surface operations. However, the RSM algorithm can be implemented as a separate program to run on any aircraft with traffic data link capability. The report documents the RSM software and describes in detail how RSM performs runway incursion detection and alerting functions for NASA RIPS. The report also describes the RIPS flight tests conducted at the Dallas-Ft Worth International Airport (DFW) during September and October of 2000, and the RSM performance results and lessons learned from those flight tests.

Green, David F., Jr.↗