A Distributionally Robust Approach for Mixed Aleatory and Epistemic Uncertainties Propagation

verfasst von

Masaru Kitahara, Jingwen Song, Pengfei Wei, Matteo Broggi, Michael Beer

Abstract

A study focuses on the generalized global non-intrusive imprecise stochastic simulation (NISS) method, as it can propagate both the imprecise probability models and nonprobabilistic models at the same time. The staircase distributions are theoretically ready to be used in this method by constructing parametric p-boxes defining their hyper parameters as interval values. The feasibility of the proposed method is demonstrated by solving the reliability analysis subproblem of the NASA uncertainty quantification (UQ) challenge problem 2019. The Gaussian distribution-based p-box naturally contains Gaussian distributions, whereas the staircase distribution-based p-box contains a broad range of distributions, including skewed and bimodal distributions. A hybrid NISS method is developed, where the staircase distribution-based p-boxes are propagated by the local NISS method to significantly suppress the computational cost to estimate the component functions over the hyperparameters.

Organisationseinheit(en)

Institut für Risiko und Zuverlässigkeit

Externe Organisation(en)

Northwestern Polytechnical University

Typ

Artikel

Journal

AIAA journal

Band

60

Seiten

4471-4477

Anzahl der Seiten

7

ISSN

0001-1452

Publikationsdatum

10.04.2022

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Luft- und Raumfahrttechnik

Elektronische Version(en)

https://doi.org/10.2514/1.J061394 (Zugang: Geschlossen)