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HIGHLIGHTS ARCHIVE
02.05.08 Division Highlights

Contents
New Approach for Sequential Traffic Flow Optimization: A new approach for traffic flow optimization given uncertainty in airspace capacity and traffic demand has been developed, and preliminary testing has been conducted using a weather impacted traffic scenario. A deterministic integer programming model assigns strategic departure delays based on traffic demand and weather-related capacity constraints. These departure delays are then applied to a real-time simulation, which uses an integer programming-based shortest path routing algorithm and an airborne holding algorithm to refine the strategic plan in the presence of weather and traffic uncertainties. This integrated approach for dealing with flow management uncertainty is believed to be unique, and represents a significant advancement to the state-of-the-art in addressing uncertainty in traffic flow management.

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Second Version of the Convective Weather Avoidance Model Completed: The MIT/Lincoln Laboratory Convective Weather Avoidance Model – 2 (CWAM-2), created with support from NASA Ames, is complete. This model provides a method to translate the impact of convective weather constraints on aircraft flights so as to estimate airspace capacity. CWAM-2 will also be used to develop more useful aircraft routing algorithms around convective weather. This model is based on the first convective weather avoidance modeling study (CWAM-1) from 2006, which used 2000 weather encounters from three Air Route Traffic Control Centers over six days. This new study evaluated data in more Centers and used more than four times the flight data. CWAM-1 only looked at flights in Indianapolis Center. Flight deviations were identified using flight track data and deviation predictors from radar derived weather data. Flight deviation predictors included vertical structure of convective activity, storm motion, and echo top growth. CWAM-2 confirmed results of the CWAM-1 study that the difference between flight altitude and echo top height is an important predictor of pilot deviation around convective weather in en-route airspace. However, storm growth did not emerge as one of the strong predictors in this study, but a further analysis of the data is planned. Surveys revealed that pilots pay attention to storm growth to determine the permeability of a storm. Prediction errors were greatest for aircraft whose flight altitude was near or slightly below the echo top height. This study showed the differentiation between 'benign' echo tops and those that pilots avoid remains the major challenge in convective weather avoidance modeling. Areas of future work include improving the deviation detection algorithm to produce more data, reviewing existing storm echo top data to determine storm growth, and consideration of human factors such as company procedures as possible deviation predictors.

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Surface Management System Model Re-architecture: NASA surface researchers met with Mosaic ATM developers to discuss design and implementation issues of the Surface Management System (SMS) Model re-architecture. Mosaic ATM is modifying the SMS architecture to support plug-ins for major model functions. The plug-in module capability will increase configurability and provide control over execution. NASA surface researchers will now be able to more easily develop and evaluate their advanced surface algorithms using SMS. A number of plug-in interfaces will be delivered by the end of February, including a compliance monitor, airport configuration advisory generator, trajectory predictor, pushback estimator, taxi scheduler, and runway scheduler.

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Helicopter Safety Monitor Evaluation in High Fidelity Simulation: New safety monitor concepts and algorithms for the Army/NASA variable stability JUH-60 helicopter (known as the Rotorcraft Aircrew-Systems Concepts Airborne Laboratory or RASCAL) were evaluated on the Vertical Motion Simulator (VMS). This new safety monitor will allow the helicopter to operate with the research flight control system (RFCS) engaged to touchdown with an acceptable level of flight safety risk. The present safety monitor disengages the research flight control system at low altitude, before touchdown, and this does not allow the investigation of guidance methods and displays to assist pilots while landing in degraded visual conditions such as brownout. The simulation required integration of software from various sources and platforms. Software from the RASCAL Development Facility as well as new code written for this experiment was integrated with the VMS real-time environment. The simulation was configured to represent both the research pilot and safety pilot functions to investigate the transfer of control between them based on the safety monitor trigger. The safety pilot flew the standard UH-60 helicopter model with motion on the VMS. The research pilot flew the RASCAL RFCS via a desktop set of inceptors in the lab. The RASCAL RFCS model commanded the helicopter model and also backdrove the controls in the cockpit. One of the challenges for this simulation was ensuring that the transitions between the baseline configuration and RFCS were transient free even when the control switch occurred during a failure or after large pilot inputs. All the necessary software and hardware components necessary for the simulation were integrated and tested successfully and the safety monitor logic was improved through evaluations with Army pilots. A follow-on simulation is scheduled for later in the year to further refine and test the safety monitor logic before it is implemented on the actual helicopter.

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