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09.18.07 Division Highlights

Climb Uncertainty Primary Cause of Unresolved Conflicts in Automated Separation Assurance: The automatic traffic conflict resolution logic developed in fast-time simulation has been merged into the Center/TRACON Automation System for real-time simulation and for analysis under conditions where trajectory uncertainty is comparable to that of today's operations. Recent analysis has focused on the performance of automatic detection and resolution for conflicts predicted in all Fort Worth Center airspace above 24,000 feet (FL240). Many conflicts in this airspace involve aircraft climbing out of the Dallas/Fort Worth International Airport or other nearby airports such as Houston Intercontinental. Typically 60% of conflicts involve climbing or descending aircraft while 40% involve both aircraft in level flight. Test results have revealed that the majority of unresolved strategic conflicts are due to late (< 3 minutes to loss of separation) conflict detections resulting from trajectory prediction errors for climbing aircraft. Airspeed, weight, thrust, and winds are all important factors in climb trajectory predictions. These results point to the need for a better understanding of how these parameters could be modeled, estimated, or datalinked to improve climb predictions and ultimately improve automated separation assurance performance for the NextGen operations.

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Simulation Investigating Crew Procedures for Trajectory Negotiation: A simulation study, representing a joint effort between the NGATS-Airspace Project and the Intelligent Integrated Flight Deck Project, got underway at the Boeing 747-400 simulator at NASA Ames Research Center the week of September 10. The goal of this simulation is to examine the use of current flight deck technology and procedures when handling trajectory negotiation clearances. The crew procedures involve receiving, reviewing, and responding to trajectory clearances via data link communications. Three B-747-400 qualified crews participated in the simulation during the week of September 10; by the end of September, data will be collected from a total of five crews. These data will be used to determine guidelines for trajectory negotiation crew procedures for a future experiment in the Spring of 2008.

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Analysis and Modeling of Taxi-Times: Taxi times between the passenger terminals and each runway at Dallas-Fort Worth airport were analyzed and modeled. Models of taxi times as a function of airport congestion are important inputs for departure scheduling. Data from the Bureau of Transportation Statistics was used to provide data on taxi duration. The runway used by each aircraft was determined from track data collected by the Surface Management System. A measure of the congestion "experienced" by a given departing flight is the number of aircraft taxiing on the same general route (i.e., from the passenger terminals to the same runway) at the time of that flight's pushback. A similar measure can be defined for arriving flights, considering the number of aircraft taxiing between the runway used by that flight and the passenger terminals, at the time of landing of that flight. The distribution of taxi times as a function of that measure of congestion are graphed for each runway, as well as the distribution of taxi times for a given level of congestion and a given runway. The preliminary results show that the latter distribution can be approximated by lognormal or normal distributions. Using those distributions, uncertainty in the departure scheduling problem can be accounted for in a well-established framework.

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Contributed to completion of the final report of the Weather – ATM Working Group of the FAA Research, Engineering and Development Advisory Committee (REDAC): This group was comprised of staff from NASA, FAA, academia, airline companies, and aviation meteorology organizations. According to the report, the objectives of the twelve-month study included examining the potential benefits associated with a higher degree of integration between two dissimilar and fundamentally inexact sciences, namely, weather and air traffic management, and with providing specific research recommendations to the FAA that were considered most likely to lead to better, more efficient ATM solutions, in the face of weather constraints. The following are some key findings cited in the report. Based on an analysis of several 2005-2006 convective events, as much as two-thirds of the weather related delay is potentially avoidable. The study also finds that a risk management approach with adaptive, incremental decision making, based on automatically translating weather forecasts into air traffic impacts, presents a major new opportunity for reducing weather related delays in the future NAS. Recommendations as described in the study include initiating a crosscutting research program in ATM/Weather integration, establishing Senior Leadership over-sight and REDAC monitoring, revitalizing joint FAA-NASA advisory committee reviews of research including weather – ATM integration, and developing Aviation Weather Research Program requirements to support integration efforts.

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SESO Deliverables: The Safe and Efficient Surface Operations (SESO) project signed off on all Task One deliverables from Virtual Airspace Simulation Technology (VAST), the real time simulation environment supporting ATM surface automation work. These deliverables include documentation, requirements, and capabilities in support of Airportal Project milestones.

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Initial JPDO Air Navigation Services Working Group Meeting: Tom Davis (Aviation Systems Division Deputy Chief) attended the initial meeting of the newly formed Air Navigation Services Working Group at the JPDO in Washington. The meeting was limited to addressing administrative and organizational issues with the functions of the working group. NASA offered to provide technical presentations on our research to aid in the development of the JPDO ConOps and other documents. NASA also offered to host future meetings in order to bring the document writers in direct contact with the researchers and their work.

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Last Updated: November 7, 2018

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