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A decomposition-based uncertainty quantification approach for environmental impacts of aviation technology and operation

Published online by Cambridge University Press:  03 August 2017

Sergio Amaral ,
Douglas Allaire ,
Elena De La Rosa Blanco  and
Karen E. Willcox
Sergio Amaral
Affiliation:
Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Douglas Allaire
Affiliation:
Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Elena De La Rosa Blanco
Affiliation:
Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
Karen E. Willcox*
Affiliation:
Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
*
Reprint requests to: Karen E. Willcox, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA. E-mail: [email protected]
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Abstract

As a measure to manage the climate impact of aviation, significant enhancements to aviation technologies and operations are necessary. When assessing these enhancements and their respective impacts on the climate, it is important that we also quantify the associated uncertainties. This is important to support an effective decision and policymaking process. However, such quantification of uncertainty is challenging, especially in a complex system that comprises multiple interacting components. The uncertainty quantification task can quickly become computationally intractable and cumbersome for one individual or group to manage. Recognizing the challenge of quantifying uncertainty in multicomponent systems, we utilize a divide-and-conquer approach, inspired by the decomposition-based approaches used in multidisciplinary analysis and optimization. Specifically, we perform uncertainty analysis and global sensitivity analysis of our multicomponent aviation system in a decomposition-based manner. In this work, we demonstrate how to handle a high-dimensional multicomponent interface using sensitivity-based dimension reduction and a novel importance sampling method. Our results demonstrate that the decomposition-based uncertainty quantification approach can effectively quantify the uncertainty of a feed-forward multicomponent system for which the component models are housed in different locations and owned by different groups.

Keywords

Aviation Environmental ImpactDecompositionGlobal Sensitivity AnalysisUncertainty Quantification
Type
Special Issue Articles
Information
AI EDAM , Volume 31 , Special Issue 3: Uncertainty Quantification for Engineering Design , August 2017 , pp. 251 - 264
Copyright
Copyright © Cambridge University Press 2017 

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