A Two-Phase Sampling Approach for Reliability-Based Optimization in Structural Engineering

verfasst von

Danko J. Jerez, Hector A. Jensen, Michael Beer

Abstract

This work presents a two-phase sampling approach to address reliability-based optimization problems in structural engineering. The constrained optimization problem is converted into a sampling problem, which is then solved using Markov chain Monte Carlo methods. First, an exploration phase generates uniformly distributed feasible designs. Thereafter, an exploitation phase is carried out to obtain a set of close-to-optimal designs. The approach is general in the sense that it is not limited to a particular type of system behavior and, in addition, it can handle constrained and unconstrained formulations as well as discrete–continuous design spaces. Three numerical examples involving structural dynamical systems under stochastic excitation are presented to illustrate the capabilities of the approach.

Organisationseinheit(en)

Institut für Risiko und Zuverlässigkeit

Externe Organisation(en)

Universidad Tecnica Federico Santa Maria
Tongji University
The University of Liverpool

Typ

Beitrag in Buch/Sammelwerk

Seiten

21-48

Anzahl der Seiten

28

Publikationsdatum

2023

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Sicherheit, Risiko, Zuverlässigkeit und Qualität

Elektronische Version(en)

https://doi.org/10.1007/978-3-031-28859-3_2 (Zugang: Geschlossen)