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HIGHLIGHTS ARCHIVE
Division Highlights


Evaluation of Conceptual Airship Design in the Vertical Motion Simulator (VMS)
August 1, 2014

Photo of a pilot in the VMS.
A pilot performs handling quality evaluations for an innovative airship concept in the Vertical Motion Simulator.

During the week of June 16, 2014, NASA Ames Research Center's Vertical Motion Simulator (VMS) hosted a simulation evaluation of an innovative airship concept proposed by LTA Corporation. The Systems Analysis Office (Code AA) conducted a Computational Fluid Dynamics (CFD) analysis and generated extensive aerodynamic data. The SimLabs branch (Code AFS) created the airship simulation incorporating Code AA's aerodynamic data with a modified version of a recently-developed, in-house Generic Airship Model Simulation (GAMS) framework, with a flight control system designed by MicroFlight, and flight instrument displays developed by VMS personnel for low-speed aircraft and tuned for typical airship maneuvers. Two pilots, one with extensive airship experience and one with extensive test pilot experience, performed formal handling quality evaluations. The test matrix included an approach to hover task with variations that comprised turbulence, constant wind, dynamic wind, positive heaviness and no Stability Augmentation System (SAS), as well as one nominal departure from hover task. Initial evaluations prompted adjustments to the flight control system which then resulted in favorable handling quality ratings. Video recordings were collected for researchers to examine the airship's performance. This simulation experiment was very useful in providing an initial assessment of a new airship design and the researchers have indicated their desire to use VMS for future pilot-in-the-loop performance test and evaluation. (POC: Emily Lewis)


Technical Interchange on Machine Learning for Automated Separation Assurance
August 1, 2014

On July 18th, 2014, a meeting was hosted at NASA Ames Research Center to discuss future directions for highly automated separation assurance systems. Ames researchers were joined by Professor Mykel Kochendorfer of Stanford University and Professor Claire Tomlin of the University of California at Berkeley. The discussions centered around how to improve the robustness and reliability of safety critical systems by using machine learning and historical data and how to extend the current methods to handle different types of operations. Multiple different methods to extend and enhance the current research portfolio in these areas were presented, including using probabilistic inference, using hybrid systems in combination with system identification, and extending the methods used in developing the Airborne Collision Avoidance System-X (ACASx) to longer time horizons. The exchange was useful and informative as we prepare to chart the course for robust and efficient autonomous separation-assurance systems. (POC: Todd Lauderdale)


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