TY - GEN
T1 - Flight safety margin theory - a theory for the engineering analysis of flight safety
AU - Jing, Hung Sying
AU - Sheng, Chia Sheng
AU - Lin, Yu Feng
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2015
Y1 - 2015
N2 - Flight Safety Margin, based on the situation of flight and from an operation point of view, provides a new tool whereby flight safety can be analyzed numerically. The flight operation is viewed moving on a virtual terrain in the abstract situation space. Any normal real flight will thus be delineated by a time-varying continuous curve around the centerline defined by the standard flight condition. The flight safety margin describing how far the present flight situation is from the accident boundary is de-fined as the inverse of the needed performance of the crew to recover the present situation back to the standard condition and scaled from zero to one. A questionnaire is designed to measure the perceived needed performance. With the chosen situation parameters as the inputs, the surveyed results are then converted to the flight safety margin, representing the outputs of the training examples. The expert sys-tem using neural network can thus provide the quantitative flight safety margin given situation parameters from real flight condition. The present methodology has been tested with the FOQA data from final approach in real cases including the Nagoya and Da-Yuang accidents. Meaningful results are obtained although there is still much room for improvement.
AB - Flight Safety Margin, based on the situation of flight and from an operation point of view, provides a new tool whereby flight safety can be analyzed numerically. The flight operation is viewed moving on a virtual terrain in the abstract situation space. Any normal real flight will thus be delineated by a time-varying continuous curve around the centerline defined by the standard flight condition. The flight safety margin describing how far the present flight situation is from the accident boundary is de-fined as the inverse of the needed performance of the crew to recover the present situation back to the standard condition and scaled from zero to one. A questionnaire is designed to measure the perceived needed performance. With the chosen situation parameters as the inputs, the surveyed results are then converted to the flight safety margin, representing the outputs of the training examples. The expert sys-tem using neural network can thus provide the quantitative flight safety margin given situation parameters from real flight condition. The present methodology has been tested with the FOQA data from final approach in real cases including the Nagoya and Da-Yuang accidents. Meaningful results are obtained although there is still much room for improvement.
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U2 - 10.1007/978-3-319-20373-7_36
DO - 10.1007/978-3-319-20373-7_36
M3 - Conference contribution
AN - SCOPUS:84947252188
SN - 9783319203720
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 377
EP - 387
BT - Engineering Psychology and Cognitive Ergonomics - 12th International Conference, EPCE 2015 Held as Part of HCI International 2015, Proceedings
A2 - Harris, Don
PB - Springer Verlag
T2 - 12th International Conference on Engineering Psychology and Cognitive Ergonomics, EPCE 2015 Held as Part of 17th International Conference on Human-Computer Interaction, HCI International 2015
Y2 - 2 August 2015 through 7 August 2015
ER -