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The engineering design process is a complex, iterative process through which individuals and teams solve ill-defined, multidisciplinary problems by integrating domain-based technical knowledge. Aerospace engineering integrates technical components from many different disciplines, such as aerodynamics, combustion, avionics, materials science, structural analysis, flight mechanics, optimization, and manufacturing.
People often make decisions without gathering or processing all possible information. Time pressure, high information acquisition costs, too much information, and incomplete information in the environment, all contribute to this reality. This thesis is motivated by the need for decision support tools for these heuristic decision makers. The foundational contributions will be a new understanding of heuristic decision making with incomplete information and how to use this knowledge to design a heuristic decision support tool.
Dr. Karen Feigh presented work on behalf of the IML team including Dr. Andrea Thomaz, Dr. Charles Isbell and Dr. Mark Riedl. Four studies were presented:
MS Thesis Defense
Supporting General Aviation Pilots During Rerouting Process Due to Sudden Weather Changes
Presentation given at IEEE Aerospace Conference 2015 in Big Sky, MT
This poster was presented at the National Robotics Initiative Principal Investigators (NRI PI) meeting on November 19-20, 2014 in Washington, D.C.
This study was presented for Brown Bag Lunch Seminar series of the School of Aerospace Engineering on September 19, 2014.
DEVELOPING A COMPUTATIONAL MODEL OF THE PILOT’S BEST POSSIBLE EXPECTATION OF AIRCRAFT STATE GIVEN VESTIBULAR AND VISUAL CUES
This thesis focuses on estimating faults in complex large-scale integrated aircraft systems, especially where they interact with, and control, the aircraft dynamics. A general assumption considered in the reliability of such systems is that any component level fault will be monitored, detected and corrected by some fault management capability.
Cognitive Engineering Center (CEC) Georgia Institute of Technology 270 Ferst Drive Atlanta GA 30332-0150
