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Uncertainty quantification of an Aviation Environmental Toolsuite

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  • Allaire, Douglas
  • Noel, George
  • Willcox, Karen
  • Cointin, Rebecca

Abstract

This paper describes uncertainty quantification (UQ) of a complex system computational tool that supports policy-making for aviation environmental impact. The paper presents the methods needed to create a tool that is “UQ-enabled†with a particular focus on how to manage the complexity of long run times and massive input/output datasets. These methods include a process to quantify parameter uncertainties via data, documentation and expert opinion, creating certified surrogate models to accelerate run-times while maintaining confidence in results, and executing a range of mathematical UQ techniques such as uncertainty propagation and global sensitivity analysis. The results and discussion address aircraft performance, aircraft noise, and aircraft emissions modeling.

Suggested Citation

  • Allaire, Douglas & Noel, George & Willcox, Karen & Cointin, Rebecca, 2014. "Uncertainty quantification of an Aviation Environmental Toolsuite," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 14-24.
    • Handle: RePEc:eee:reensy:v:126:y:2014:i:c:p:14-24
    DOI: 10.1016/j.ress.2014.01.002
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    References listed on IDEAS

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    1. Allaire, Douglas L. & Willcox, Karen E., 2012. "A variance-based sensitivity index function for factor prioritization," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 107-114.
    2. Baratelli, Fulvia & Giudici, Mauro & Vassena, Chiara, 2012. "A sensitivity analysis for an evolution model of the Antarctic ice sheet," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 64-70.
    3. Marco Ratto, 2008. "Analysing DSGE Models with Global Sensitivity Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 31(2), pages 115-139, March.
    4. Helton, Jon C. & Hansen, Clifford W. & Sallaberry, Cédric J., 2012. "Uncertainty and sensitivity analysis in performance assessment for the proposed high-level radioactive waste repository at Yucca Mountain, Nevada," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 44-63.
    5. Cooke, Roger M. & Goossens, Louis L.H.J., 2008. "TU Delft expert judgment data base," Reliability Engineering and System Safety, Elsevier, vol. 93(5), pages 657-674.
    6. Zentner, Irmela & Tarantola, Stefano & de Rocquigny, E., 2011. "Sensitivity analysis for reliable design verification of nuclear turbosets," Reliability Engineering and System Safety, Elsevier, vol. 96(3), pages 391-397.
    7. Oladyshkin, S. & Nowak, W., 2012. "Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 179-190.
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    Cited by:

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