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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Extending a Flight Management Computer for Simulation and Flight Experiments

In modern transport aircraft, the flight management computer (FMC) has evolved from a flight planning aid to an important hub for pilot information and origin-to-destination optimization of flight performance. Current trends indicate increasing roles of the FMC in aviation safety, aviation security, increasing airport capacity, and improving environmental impact from aircraft. Related research conducted at the Langley Research Center (LaRC) often requires functional extension of a modern, full-featured FMC. Ideally, transport simulations would include an FMC simulation that could be tailored and extended for experiments. However, due to the complexity of a modern FMC, a large investment (millions of dollars over several years) and scarce domain knowledge are needed to create such a simulation for transport aircraft. As an intermediate alternative, the Flight Research Services Directorate (FRSD) at LaRC created a set of reusable software products to extend flight management functionality upstream of a Boeing-757 FMC, transparently simulating or sharing its operator interfaces. The paper details the design of these products and highlights their use on NASA projects.

Madden, Michael M.↗
NASA NTRS2014

Flightdeck Automation Problems (FLAP) Model for Safety Technology Portfolio Assessment

NASA's Aviation Safety Program (AvSP) develops and advances methodologies and technologies to improve air transportation safety. The Safety Analysis and Integration Team (SAIT) conducts a safety technology portfolio assessment (PA) to analyze the program content, to examine the benefits and risks of products with respect to program goals, and to support programmatic decision making. The PA process includes systematic identification of current and future safety risks as well as tracking several quantitative and qualitative metrics to ensure the program goals are addressing prominent safety risks accurately and effectively. One of the metrics within the PA process involves using quantitative aviation safety models to gauge the impact of the safety products. This paper demonstrates the role of aviation safety modeling by providing model outputs and evaluating a sample of portfolio elements using the Flightdeck Automation Problems (FLAP) model. The model enables not only ranking of the quantitative relative risk reduction impact of all portfolio elements, but also highlighting the areas with high potential impact via sensitivity and gap analyses in support of the program office. Although the model outputs are preliminary and products are notional, the process shown in this paper is essential to a comprehensive PA of NASA's safety products in the current program and future programs/projects.

Ancel, Ersin↗
NASA NTRS2016

Psychophysiological Sensing and State Classification for Attention Management in Commercial Aviation

Attention-related human performance limiting states (AHPLS) can cause pilots to lose airplane state awareness (ASA), and their detection is important to improving commercial aviation safety. The Commercial Aviation Safety Team found that the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness, and that distraction of various forms was involved in all of them. Research on AHPLS, including channelized attention, diverted attention, startle / surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors has been implemented to simultaneously measure their physiological markers during high fidelity flight simulation human subject studies. Pilot participants were asked to perform benchmark tasks and experimental flight scenarios designed to induce AHPLS. Pattern classification was employed to distinguish the AHPLS induced by the benchmark tasks. Unimodal classification using pre-processed electroencephalography (EEG) signals as input features to extreme gradient boosting, random forest and deep neural network multiclass classifiers was implemented. Multi-modal classification using galvanic skin response (GSR) in addition to the same EEG signals and using the same types of classifiers produced increased accuracy with respect to the unimodal case (90 percent vs. 86 percent), although only via the deep neural network classifier. These initial results are a first step toward the goal of demonstrating simultaneous real time classification of multiple states using multiple sensing modalities in high-fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents.

Harrivel, Angela R.↗
NASA NTRS1997

A Practical Guide to Interpretation of Large Collections of Incident Narratives Using the QUORUM Method

Analysis of incident reports plays an important role in aviation safety. Typically, a narrative description, written by a participant, is a central part of an incident report. Because there are so many reports, and the narratives contain so much detail, it can be difficult to efficiently and effectively recognize patterns among them. Recognizing and addressing recurring problems, however, is vital to continuing safety in commercial aviation operations. A practical way to interpret large collections of incident narratives is to apply the QUORUM method of text analysis, modeling, and relevance ranking. In this paper, QUORUM text analysis and modeling are surveyed, and QUORUM relevance ranking is described in detail with many examples. The examples are based on several large collections of reports from the Aviation Safety Reporting System (ASRS) database, and a collection of news stories describing the disaster of TWA Flight 800, the Boeing 747 which exploded in mid- air and crashed near Long Island, New York, on July 17, 1996. Reader familiarity with this disaster should make the relevance-ranking examples more understandable. The ASRS examples illustrate the practical application of QUORUM relevance ranking.

McGreevy, Michael W.↗
NASA NTRS2001

Market Assessment of Forward-Looking Turbulence Sensing Systems

In recognition of the importance of turbulence mitigation as a tool to improve aviation safety, NASA's Aviation Safety Program developed a Turbulence Detection and Mitigation Sub-element. The objective of this effort is to develop highly reliable turbulence detection technologies for commercial transport aircraft to sense dangerous turbulence with sufficient time warning so that defensive measures can be implemented and prevent passenger and crew injuries. Current research involves three forward sensing products to improve the cockpit awareness of possible turbulence hazards. X-band radar enhancements will improve the capabilities of current weather radar to detect turbulence associated with convective activity. LIDAR (Light Detection and Ranging) is a laser-based technology that is capable of detecting turbulence in clear air. Finally, a possible Radar-LIDAR hybrid sensor is envisioned to detect the full range of convective and clear air turbulence. To support decisions relating to the development of these three forward-looking turbulence sensor technologies, the objective of this study was defined as examination of cost and implementation metrics. Tasks performed included the identification of cost factors and certification issues, the development and application of an implementation model, and the development of cost budget/targets for installing the turbulence sensor and associated software devices into the commercial transport fleet.

Kauffmann, Paul↗
NASA NTRS2010

Aircraft Loss of Control Study

Loss of control has become the leading cause of jet fatalities worldwide. Aside from their frequency of occurrence, accidents resulting from loss of aircraft control seize the public s attention by yielding large numbers of fatalities in a single event. In response to the rising threat to aviation safety, NASA's Aviation Safety Program has conducted a study of the loss of control problem. This study gathered four types of information pertaining to loss of control accidents: (1) statistical data; (2) individual accident reports that cite loss of control as a contributing factor; (3) previous meta-analyses of loss of control accidents; and (4) inputs solicited from aircraft manufacturers, air carriers, researchers, and other industry stakeholders. Using these information resources, the study team identified causal factors that were cited in the greatest number of loss of control accidents, and which were emphasized most by industry stakeholders. For each causal factor that was linked to loss of control, the team solicited ideas about what solutions are required and future research efforts that could potentially help avoid their occurrence or mitigate their consequences when they occurred in flight.

Jacobson, Steven R.↗
NASA NTRS2010

Aircraft Loss of Control Causal Factors and Mitigation Challenges

Loss of control is the leading cause of jet fatalities worldwide. Aside from their frequency of occurrence, accidents resulting from loss of aircraft control seize the public s attention by yielding a large number of fatalities in a single event. In response to the rising threat to aviation safety, the NASA Aviation Safety Program has conducted a study of the loss of control problem. This study gathered four types of information pertaining to loss of control accidents: (1) statistical data; (2) individual accident reports that cite loss of control as a contributing factor; (3) previous meta-analyses of loss of control accidents; and (4) inputs solicited from aircraft manufacturers, air carriers, researchers, and other industry stakeholders. Using these information resources, the study team identified the causal factors that were cited in the greatest number of loss of control accidents, and which were emphasized most by industry stakeholders. This report describes the study approach, the key causal factors for aircraft loss of control, and recommended mitigation strategies to make near-term impacts, mid-term impacts, and Next Generation Air Transportation System impacts on the loss of control accident statistics

Jacobson, Steven R.↗
NASA NTRS2001

Satellite Delivery of Aviation Weather Data

With aviation traffic continuing to increase worldwide, reducing the aviation accident rate and aviation schedule delays is of critical importance. In the United States, the National Aeronautics and Space Administration (NASA) has established the Aviation Safety Program and the Aviation System Capacity Program to develop and test new technologies to increase aviation safety and system capacity. Weather is a significant contributor to aviation accidents and schedule delays. The timely dissemination of weather information to decision makers in the aviation system, particularly to pilots, is essential in reducing system delays and weather related aviation accidents. The NASA Glenn Research Center is investigating improved methods of weather information dissemination through satellite broadcasting directly to aircraft. This paper describes an on-going cooperative research program with NASA, Rockwell Collins, WorldSpace, Jeppesen and American Airlines to evaluate the use of satellite digital audio radio service (SDARS) for low cost broadcast of aviation weather information, called Satellite Weather Information Service (SWIS). The description and results of the completed SWIS Phase 1 are presented, and the description of the on-going SWIS Phase 2 is given.

Kerczewski, Robert J.↗
NASA NTRS2013

Identification of Crew-Systems Interactions and Decision Related Trends

NASA Vehicle System Safety Technology (VSST) project management uses systems analysis to identify key issues and maintain a portfolio of research leading to potential solutions to its three identified technical challenges. Statistical data and published safety priority lists from academic, industry and other government agencies were reviewed and analyzed by NASA Aviation Safety Program (AvSP) systems analysis personnel to identify issues and future research needs related to one of VSST's technical challenges, Crew Decision Making (CDM). The data examined in the study were obtained from the National Transportation Safety Board (NTSB) Aviation Accident and Incident Data System, Federal Aviation Administration (FAA) Accident/Incident Data System and the NASA Aviation Safety Reporting System (ASRS). In addition, this report contains the results of a review of safety priority lists, information databases and other documented references pertaining to aviation crew systems issues and future research needs. The specific sources examined were: Commercial Aviation Safety Team (CAST) Safety Enhancements Reserved for Future Implementation (SERFIs), Flight Deck Automation Issues (FDAI) and NTSB Most Wanted List and Open Recommendations. Various automation issues taxonomies and priority lists pertaining to human factors, automation and flight design were combined to create a list of automation issues related to CDM.

Jones, Sharon Monica↗