Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5925
Title: Reliability estimation using univariate dimension reduction and extended generalised lambda distribution
Authors: Acar, Erdem
Rais-Rohani, Masoud
Eamon, C. D.
Keywords: Dimension reduction
Distribution fitting
EGLD
Extended generalised lambda distribution
Reliability analysis
Statistical moment matching
Issue Date: 2010
Publisher: Inderscience Publishers
Abstract: This paper presents an analytical approach for structural reliability analysis without requiring the calculation of most probable point of failure. Initially, the primary statistical moments of a multi-dimensional performance function are estimated using the Univariate Dimension-Reduction (UDR) methodology based on additive decomposition of the limit state function. Through moment matching, the UDR-based estimated moments are then used to fit the parameters of Extended Generalised Lambda Distribution (EGLD), and finally the probability of failure is calculated. To evaluate the accuracy and efficiency of the UDR + EGLD approach in comparison to the traditional First-Order Reliability Method (FORM) and direct Monte Carlo Simulation (MCS), five example problems involving nonlinear limit state functions areexamined. The results show that UDR + EGLD offers nearly the same level of accuracy as MCS with superior efficiency to FORM. However, UDR + EGLD appears to have tail sensitivity, which limits its application to problems with moderate levels of reliability. Copyright © 2010 Inderscience Enterprises Ltd.
URI: https://doi.org/10.1504/IJRS.2010.032444
https://hdl.handle.net/20.500.11851/5925
ISSN: 1479-389X
Appears in Collections:Makine Mühendisliği Bölümü / Department of Mechanical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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