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https://doi.org/10.2514/6.2013...
Article . 2013 . Peer-reviewed
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Stochastic Drag Analysis via Polynomial Chaos Uncertainty Quantification

Authors: Wataru YAMAZAKI;

Stochastic Drag Analysis via Polynomial Chaos Uncertainty Quantification

Abstract

In this paper, uncertainty quantification approaches are applied to aerodynamic data analyzed by a far-field drag breakdown approach. By the use of the drag breakdown approach, total drag of an airfoil configuration can be decomposed into three physical and one unphysical drag components, that are wave, viscous, induced and spurious drag components. The drag source distribution can also be visualized on the flowfield by using this approach. An uncertainty quantification problem of 2D airfoil is analyzed with the drag breakdown approach to extract more aerodynamic design information about its uncertainty propagation. Two uncertainty quantification approaches, non-intrusive polynomial chaos approach and inexpensive Monte Carlo simulation approach on a response surface model, are investigated for more advanced uncertainty quantification of an aerodynamic problem.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Top 10%
Top 10%
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