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

verfasst von

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.

Organisationseinheit(en)

Institut für Risiko und Zuverlässigkeit
Internationales GRK 2657: Methoden der Numerischen Mechanik in höheren Dimensionen
SFB 871: Regeneration komplexer Investitionsgüter

Externe Organisation(en)

The University of Liverpool
Tongji University

Typ

Artikel

Journal

Engineering structures

Band

312

ISSN

0141-0296

Publikationsdatum

01.08.2024

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Tief- und Ingenieurbau

Elektronische Version(en)

https://doi.org/10.1016/j.engstruct.2024.118210 (Zugang: Offen)