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

authored by

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.

Organisation(s)

Institute for Risk and Reliability

External Organisation(s)

Universidad Tecnica Federico Santa Maria
Tongji University
University of Liverpool

Type

Contribution to book/anthology

Pages

21-48

No. of pages

28

Publication date

2023

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality

Electronic version(s)

https://doi.org/10.1007/978-3-031-28859-3_2 (Access: Closed)