Optimization of Structures Subject to Stochastic Dynamic Loading

Jiaqi Xu, Billie F. Spencer, Xilin Lu, Xinzhong Chen, Lei Lu

Research output: Contribution to journalArticle

Abstract

Structural optimization has progressed substantially over the last half century. However, the literature on optimization of structures under random excitation is limited. This study provides a framework for structural optimization subject to stochastic dynamic loading. Illustrative examples of structures under nonstationary seismic and stationary wind loads are presented to demonstrate the procedure. Both safety and serviceability are considered concurrently. The objective function for safety is given in terms of both harmful interstory drift and harmful interstory drift angle; whereas for serviceability, the objective function is defined in terms of floor acceleration. Safety and serviceability are shown to be competing objectives under both seismic and wind excitation; however, the contrast is less under wind excitation. The proposed optimization framework provides a rational manner in which engineering design tradeoffs can be made between the two competing objectives.

Original languageEnglish (US)
Pages (from-to)657-673
Number of pages17
JournalComputer-Aided Civil and Infrastructure Engineering
Volume32
Issue number8
DOIs
StatePublished - Aug 2017

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Structural optimization

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics

Cite this

Optimization of Structures Subject to Stochastic Dynamic Loading. / Xu, Jiaqi; Spencer, Billie F.; Lu, Xilin; Chen, Xinzhong; Lu, Lei.

In: Computer-Aided Civil and Infrastructure Engineering, Vol. 32, No. 8, 08.2017, p. 657-673.

Research output: Contribution to journalArticle

Xu, Jiaqi ; Spencer, Billie F. ; Lu, Xilin ; Chen, Xinzhong ; Lu, Lei. / Optimization of Structures Subject to Stochastic Dynamic Loading. In: Computer-Aided Civil and Infrastructure Engineering. 2017 ; Vol. 32, No. 8. pp. 657-673.
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