IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-031-28859-3_2.html
   My bibliography  Save this book chapter

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
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ssrchp:978-3-031-28859-3_2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.