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A -- REQUEST FOR COMMENTS FOR THE DEVELOPMENT OF PROTOTYPE(S) FOR A GLOBAL ANALYSIS AND INFORMATION NETWORK (GAIN) DOCKET NO. 28567 PART 2 OF 3 DUE 061496 POC Mr. Chuck Fluet, Manager, Safety Analysis Division, Office of Aviation Safety, ASY-200, Federal Aviation Administration, 400 7th Street, SW., Washington, DC 20590 Telephone No. 202-267-GAIN (202-267-4246) The likelihood of detecting problems and developing remedies is significantly greater from studying large numbers of normal daily operations than from relying primarily upon a far smaller number of periodic inspections or accident and incident investigations. Analysis of digital flight data can provide several types of information, including aircraft path analysis, derivation of environmental conditions, aircraft configuration time histories, aerodynamic coefficients (analysis of coefficients can reveal degradation in aerodynamic performance), engine performance, aircraft attitude, automated flight control modes and status, warning parameters, takeoff and landing distances, and flight loads. Digital flight data can be used to detect single anomalies -- alerting operators when criteria values for selected parameters have been exceeded or when particular events occur. Such data also can be used to develop descriptive statistics across fleets, to detect deviations from statistical norms in the aviation system, or to measure the effects of design, procedure, or equipment changes. ATC automated data could be used to analyze airplane motion and relative position, important factors in analyzing issues such as wake vortex and environmental effects. An analysis of air traffic control automated data for normal operations could provide insight into methods for improving ATC system operations or potential problem areas. Flight data anomalies from accidents could be compared to similar anomalies of flights that did not crash to learn what was done differently to avoid an accident. These findings might suggest guidelines on pilot training or aircraft design. The same autonomous ''intelligent agent'' analysis techniques used to find patterns in data from incident reporting also can be applied to digital flight data and ATC radar data -- or information derived from this data such as paths, flight loads, or aerodynamic coefficients -- to determine if any otherwise unobserved associations exist within the data. Human Factors Analysis - This analytical process and the new sources of data under consideration could significantly improve our ability to describe what is happening in the aviation system, and a comparable human factors analysis capability must also be developed. Without a reliable human factors analysis tool that addresses the underlying causes or factors associated with emerging safety concerns, remedial measures may only be temporary ''band aids.'' An effective human performance analysis capability developed for use on digital flight data or ATC automated data -- augmented by feedback from voluntary disclosure systems -- is an essential part of an early warning system. A Proposed Architecture for Sharing As noted above, for a number of reasons, not the least of which is the very large quantity of data, there will probably be little or no sharing of raw data, but only of information from the analysis of data. Moreover, because of improved networking technologies and capabilities, information would not necessarily all be sent to a massive computer at one location, but would probably be available to different users to different extents by networking -- sometimes known as a ''virtual database.'' For example, this networking capability makes it possible for each carrier, manufacturer, or union to have separate GAIN-type systems, or they could do it collectively with one or more others or through trade associations, or any combination of them, and the information sharing could occur over the network to the extent desired or permitted by the owner of each system. The information that results from GAIN analyses would ideally be available immediately to all recipients who could use it to improve aviation safety. The dissemination of vital information can be accomplished with existing infrastructure -- using the Internet, for example, if adequate safeguards can be provided to protect the security and confidentiality concerns of the information providers regarding identified or identifiable data. The GAIN network would have to accommodate different requirements in a user-friendly way, and be able to notify automatically all appropriate recipients about potential problems without requiring them to know to query the system. Examples of Proactive Use of Aviation Safety Data There are several examples in various countries that demonstrate how effectively proactive safety measures can be implemented as a result of industry/labor/government partnership sharing of such information. When one air carrier's data indicated that pilots were frequently disregarding their Ground Proximity Warning System (GPWS), the carrier discovered that the frequent disregard was due to a high false alarm rate, and further analysis of the data provided the basis for developing a software remedy. As a result, that GPWS system was improved (to the benefit of all carriers that used it), the false alarm rate dropped, and pilots ignored the warning much less. Similarly, a carrier that was experiencing frequent altitude capture excursions and deviations in one of its aircraft types found from the data that the problem was a combination of inadequate pilot training and poor altitude capture logic. Analysis of the data provided the basis for improving both the training and the logic. Again, the logic fix benefited all users of that autopilot around the world, not just the carrier that discovered the problem. Other examples include improvements to training programs and/or operations manuals as a result of high pitch angle takeoffs, more rapid that desirable takeoff rotation rates, inadvertent flap/slat retraction out of the proper speed range, and unstabilized approaches; design fixes for equipment that did not perform as designed or anticipated (e.g., an aircraft that was developing cracks from hard landings at less than the 2 g cutoff beyond which inspection was mandated); and improvements in airport signs and markings to help pilots more accurately follow their taxi clearances. Also important, of course, is that without the data, it is very difficult for carriers, manufacturers, or governments to evaluate whether new programs and other fixes are having the desired result. Concept Implementation Issues Collection and Analysis of Aviation Safety Data In developing an analytical process for an early warning capability that would monitor the system and alert the aviation community to existing and emerging safety concerns, please consider what data requirements, analysis methods, and information dissemination methods you would propose. In relation to the analytical process, please consider and comment on issues such as the following: -- What aviation safety data and information are needed to support your analysis plan and what, of those needs, is not now being collected? -- Should large quantities of data be collected on a wide range of safety issues, or less data on fewer targeted safety issues? -- To what extent is standardization of the data collection or of analysis techniques necessary? How should the necessary standardization be accomplished? End Part 2 of 3. (0130)

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