Scenario-Based Risk Analysis of the UAV Flight Test

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 536-537)
• Pages: 1674-1678
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.536-537.1674
• Online since: April 2014
• Authors: Shi Jie Li, Fa Jie Wei, Jun Wei Zeng*
• Keywords: Cross Impact Analysis, Interpretive Structural Modeling, Risk Analysis, UAV Flight Test

References

[1] Eugene F. M. Y., in: UAV Flight Test System (National University of Singapore, Singapore 2008).

[2] Austin R., in: Unmanned Aircraft Systems (John Wiley & Sons, London 2010).

[3] Banuls V. A., and Salmeron J. L.: Technol. Forecast. Soc. Change, Vol. 74(2007), p.750.

[4] Gregoriades A., and Sutcliffe A.: IEEE Trans. Softw. Eng., Vol. 31(2005), p.392.

[5] Fukushima Y., and Hirao M.: Int. J. Life Cycle Assess., Vol. 7(2002), p.317.

[6] Harries C.: Technol. Forecast. Soc. Change, Vol. 70(2003), p.797.

[7] Chermack T. J.: Futures, Vol. 39(2007), p.1.

[8] Van Notten P. W. F., Rotmans J., van Asselt M. B. A., and Rothman D. S.: Futures, Vol. 35(2003), p.423.

DOI: 10.1016/s0016-3287(02)00090-3

[9] Bañuls V. A., and Turoff M.: Technol. Forecast. Soc. Change, 78(2011), p.1579.

[10] Malone D. W.: Proceedings of the IEEE (1975).

[11] Watson R. H.: Technol. Forecast. Soc. Change, Vol. 11(1978), p.165.

[12] Pfohl H. -C., Gallus P., and Thomas D.: Int. J. Phys. Distrib. Logist. Manag., Vol. 41(2011), p.839.

[13] Talib F., Rahman Z., and Qureshi M. N.: Benchmarking An Int. J., Vol. 18(2011), p.563.

[14] Singh M. D., and Kant R.: 2007 IEEE Int. Conf. Ind. Eng. Eng. Manag (2007).

[15] Turoff M., and Bañuls V.: Proceedings of the 8th International Conference on Information Systems for Crisis Response and Management, (Portugal 2011).

[16] Bañuls V. A., Turoff M., and Hiltz S. R.: Technol. Forecast. Soc. Change, Vol. 80(2013), p.1756.

[17] Turoff M., Hiltz S. R., Bañuls V. A., Van Den Eede G., and Bañuls V. A.: Technol. Forecast. Soc. Change, Vol. 80(2013), p.1647.

DOI: 10.1016/j.techfore.2013.07.014

[18] Turoff M.: Technol. Forecast. Soc. Change, Vol. 3(1972), p.309.