Bayesian parameter identification of hysteretic behavior of composite walls

Pei Liu*, Siu Kui Au

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

Abstract

A Bayesian probabilistic approach is applied for parameter identification of a hysteretic model using laboratory test data in this paper. A hysteretic model for multi-grid composite walls is proposed to model the behavior of multi-grid composite wall specimens under lateral cyclic loading. Effects of stiffness degradation, strength degradation and pinching are considered. The test data consists of observed hysteretic curves of precast composite wall specimen, composite wall specimen reinforced by light steel, retrofitted composite wall specimen and cast-in-place composite wall specimen. Using the Bayesian approach, the identification results are presented in terms of the most probable value and posterior covariance matrix of model parameters. The implied hysteretic and backbone curves with their uncertainties identified based on the test data are compared with their observed counterparts.

Original languageEnglish
Pages (from-to)101-109
Number of pages9
JournalProbabilistic Engineering Mechanics
Volume34
DOIs
Publication statusPublished - 2013
Externally publishedYes

ASJC Scopus Subject Areas

  • Statistical and Nonlinear Physics
  • Civil and Structural Engineering
  • Nuclear Energy and Engineering
  • Condensed Matter Physics
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanical Engineering

Keywords

  • Bayesian approach
  • Hysteretic model
  • Multi-grid composite walls
  • Parameter identification

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