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2019 | OriginalPaper | Chapter

Second-Order Derivatives for Geometrical Uncertainties

Authors : Marcin Wyrozębski, Łukasz Łaniewski-Wołłk, Jacek Rokicki

Published in: Uncertainty Management for Robust Industrial Design in Aeronautics

Publisher: Springer International Publishing

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Abstract

The paper presents a method for handling geometrical uncertainties. In this case, discretization of continuous uncertainty field leads to a large set of correlated uncertainties/random variables. In order to reduce dimensionality of the problem, the authors propose a method that takes advantage of both the probabilistic information (covariance) and the local behavior of the objective (up to a second-order derivatives). The proposed method is verified for the UMRIDA BC-03 test case (UMRIDA Consortium, Test case description innovative database for UQ and RDM, 2014). The method is shown to outperform the Karhunen-Loeve decomposition and the analysis based purely on the Hessian matrix. The method allows to keep the same level of accuracy with a significant reduction of the number of uncertainties.

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previous chapter Algorithmic Differentiation for Second Derivatives
next chapter Application of UQ for Turbine Blade CHT Computations
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Metadata
Title
Second-Order Derivatives for Geometrical Uncertainties
Authors
Marcin Wyrozębski
Łukasz Łaniewski-Wołłk
Jacek Rokicki
Copyright Year
2019
Book
Uncertainty Management for Robust Industrial Design in Aeronautics

Print ISBN: 978-3-319-77766-5

Electronic ISBN: 978-3-319-77767-2

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-77767-2_22

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