Efficient reliability analysis of stochastic dynamic first-passage problems by probability density evolution analysis with subset supported point selection

authored by

Marius Bittner, Matteo Broggi, Michael Beer

Abstract

This study introduces a novel point selection procedure for the Probability Density Evolution Method (PDEM) to estimate time-dependent reliability and failure probabilities in dynamic systems under first-passage failure conditions. The method integrates and modifies features of the Subset simulation procedure to adaptively generate dependent sample sets suitable for a reliability analysis by a direct probability integration approach levering PDEM. Performance function assessments are used as weighting factors in the Subset supported Point Selection (S-PS), enhancing the ultimate failure probability estimation accuracy. The presented approach effectively identifies samples in the failure region, particularly benefiting for dynamic systems under stochastic excitation, tested with random dimensions up to 60. It also offers a computationally efficient structural reliability estimation procedure by analyzing full time–history responses. The proposed method provides deeper insights into rare failure events and mechanisms through the visualization of intermediate results. This research presents an advanced framework for estimating structural reliability and understanding critical events in dynamic systems.

Organisation(s)

Institute for Risk and Reliability
International RTG 2657: Computational Mechanics Techniques in High Dimensions
CRC 871 Regeneration of Complex Capital Goods

External Organisation(s)

University of Liverpool
Tongji University

Type

Article

Journal

Engineering structures

Volume

312

ISSN

0141-0296

Publication date

01.08.2024

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Civil and Structural Engineering

Electronic version(s)

https://doi.org/10.1016/j.engstruct.2024.118210 (Access: Open)