@inproceedings{a74675f795e3456699566f5afb8f3c84,
title = "On the use of high-order statistics in robust design optimization",
abstract = "ANOVA analysis is a very common numerical technique for computing a hierarchy of most important input parameters for a given output when variations are computed in terms of variance. This second central moment can not be retained as an universal criterion for ranking some variables, since a non-Gaussian output could require higher order (more than second) statistics for a complete description and analysis. In this work, we illustrate how third and fourth-order statistic moments, i.e. skewness and kurtosis, respectively, can be decomposed. It is shown that this decomposition is correlated to a polynomial chaos expansion, permitting to easily compute each term. Then, new sensitivity indices are proposed basing on the computation of the kurtosis. Some test-cases are introduced showing the importance of high-order statistics in robust design optimization.",
keywords = "CFD, High-order statistics, Robust design optimization",
author = "Congedo, \{P. M.\} and G. Geraci and G. Iaccarino",
year = "2014",
month = jul,
day = "1",
language = "English",
series = "11th World Congress on Computational Mechanics, WCCM 2014, 5th European Conference on Computational Mechanics, ECCM 2014 and 6th European Conference on Computational Fluid Dynamics, ECFD 2014",
publisher = "International Center for Numerical Methods in Engineering",
pages = "6468--6479",
editor = "Eugenio Onate and Xavier Oliver and Antonio Huerta",
booktitle = "11th World Congress on Computational Mechanics, WCCM 2014, 5th European Conference on Computational Mechanics, ECCM 2014 and 6th European Conference on Computational Fluid Dynamics, ECFD 2014",
note = "Joint 11th World Congress on Computational Mechanics, WCCM 2014, the 5th European Conference on Computational Mechanics, ECCM 2014 and the 6th European Conference on Computational Fluid Dynamics, ECFD 2014 ; Conference date: 20-07-2014 Through 25-07-2014",
}