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Uncertainty Quantification in Aeroelasticity

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Part of the book series: Lecture Notes in Computational Science and Engineering ((LNCSE,volume 92))

Abstract

It is important to account for uncertainties in aeroelastic response when designing and certifying aircraft. However, aeroelastic uncertainties are particularly challenging to quantify, since dynamic stability is a binary property (stable or unstable) that may be sensitive to small variations in system parameters. To correctly discern stability, the interactions between fluid and structure must be accurately captured. Such interactions involve an energy flow through the interface, which if unbalanced, can destablize the structure. With conventional computational techniques, the consequences of imbalance may require large simulation times to discern, and evaluating the dependence of stability on numerous system parameters can become intractable. In this chapter, the challenges in quantifying aeroelastic uncertainties will be explored and numerical methods will be described to decrease the difficulty of quantifying aeroelastic uncertainties and increase the reliability of aircraft structures subjected to airloads. A series of aeroelastic analyses and reliability studies will be carried out to illustrate key concepts.

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Acknowledgements

The authors wish to thank Prof. Ramana Grandhi (Wright State University) for many discussions that were helpful in the preparation of this manuscript, Dr. Chris Koehler (Universal Technology Corporation) for assistance in developing manuscript graphics, and Dr. Manav Bhatia (Universal Technology Corporation) for reviewing the manuscript. This work was sponsored by the Air Force Office of Scientific Research under Laboratory Task 03VA01COR (monitored by Dr. Fariba Fahroo).

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Correspondence to Philip Beran .

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Beran, P., Stanford, B. (2013). Uncertainty Quantification in Aeroelasticity. In: Bijl, H., Lucor, D., Mishra, S., Schwab, C. (eds) Uncertainty Quantification in Computational Fluid Dynamics. Lecture Notes in Computational Science and Engineering, vol 92. Springer, Cham. https://doi.org/10.1007/978-3-319-00885-1_2

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