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

In: Advances in Reliability and Maintainability Methods and Engineering Applications

Author

Listed:
  • Danko J. Jerez

    (Leibniz Universität Hannover)

  • Hector A. Jensen

    (Federico Santa Maria Technical University)

  • Michael Beer

    (Leibniz Universität Hannover
    Tongji University
    University of Liverpool)

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.

Suggested Citation

  • Danko J. Jerez & Hector A. Jensen & Michael Beer, 2023. "A Two-Phase Sampling Approach for Reliability-Based Optimization in Structural Engineering," Springer Series in Reliability Engineering, in: Yu Liu & Dong Wang & Jinhua Mi & He Li (ed.), Advances in Reliability and Maintainability Methods and Engineering Applications, pages 21-48, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-28859-3_2
    DOI: 10.1007/978-3-031-28859-3_2
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    Cited by:

    1. Jerez, Danko J. & Chwała, M. & Jensen, Hector A. & Beer, Michael, 2024. "Optimal borehole placement for the design of rectangular shallow foundation systems under undrained soil conditions: A stochastic framework," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

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