Multifidelity Uncertainty Propagation in Coupled Multidisciplinary Systems
Name
Willcox_Multifidelity uncertainty.pdf
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2.33 MB
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Author(s)
Chaudhuri, Anirban
Willcox, Karen E
Date Issued
January 2016
Journal
Proceedings of the 18th AIAA Non-Deterministic Approaches Conference
Publisher
American Institute of Aeronautics and Astronautics
Citation
Chaudhuri, Anirban, and Karen E. Willcox. “Multifidelity Uncertainty Propagation in Coupled Multidisciplinary Systems.” American Institute of Aeronautics and Astronautics, 2016.
Version
Author's final manuscript
Abstract
Fixed point iteration is a common strategy to handle interdisciplinary coupling within a coupled multidisciplinary analysis. For each coupled analysis, this requires a large number of disciplinary high-fidelity simulations to resolve the interactions between different disciplines. When embedded within an uncertainty analysis loop (e.g., with Monte Carlo sampling over uncertain parameters) the number of high-fidelity disciplinary simulations
quickly becomes prohibitive, since each sample requires a fixed point iteration and the uncertainty analysis typically involves thousands or even millions of samples. This paper develops a method for uncertainty analysis in feedback-coupled black-box systems that leverages adaptive surrogates to reduce the number of cases for which fixed point iteration is needed. The multifidelity coupled uncertainty propagation method is an iterative process
that uses surrogates for approximating the coupling variables and adaptive sampling strategies to refine the surrogates. The adaptive sampling strategies explored in this work are residual error, information gain, and weighted information gain. The surrogate models are adapted in a way that does not compromise accuracy of the uncertainty analysis relative to the original coupled high-fidelity problem.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.2514/6.2016-1442
