Scenario-Based Risk Analysis of the UAV Flight Test
Due to high uncertainty and complexity, the flight test missions of the Unmanned Aerial Vehicle (UAV) are implemented with high risk. To mitigate the risk, many scholars have done a lot of researches to study the risk events in flight test. The different interrelations and the potential synergetic e...
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Published in | Applied Mechanics and Materials Vol. 536-537; no. Advances in Mechatronics, Robotics and Automation II; pp. 1674 - 1678 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Zurich
Trans Tech Publications Ltd
01.04.2014
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Subjects | |
Online Access | Get full text |
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Summary: | Due to high uncertainty and complexity, the flight test missions of the Unmanned Aerial Vehicle (UAV) are implemented with high risk. To mitigate the risk, many scholars have done a lot of researches to study the risk events in flight test. The different interrelations and the potential synergetic effects among the relevant risk events related to a decision make it a challenging issue to create explicit relationships of the risk events. Cross Impact Analysis (CIA) appeared as a methodological tool for dealing with this kind of complexity in the 1960’s. CIA can worked with other methodological approaches to increase its functionality. This article uses a method to generate important risk events and scenarios about what may happen in the future flight tests. In this method, Interpretive Structural Modeling (ISM) is used to combined with CIA to improve the final forecasting. This scenarios-based method allows working with large sets of risk events and can detect critical risk events. The final results of the method can be represented by graphics. The practical implications of the proposed method are illustrated with an example. |
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Bibliography: | Selected, peer reviewed papers from the 2014 2nd International Conference on Mechatronics, Robotics and Automation, (ICMRA 2014), March 8-9, 2014, Zhuhai, China ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISBN: | 9783038350781 3038350788 |
ISSN: | 1660-9336 1662-7482 1662-7482 |
DOI: | 10.4028/www.scientific.net/AMM.536-537.1674 |