Multivariate regression models in estimating the behavior of FRP tube encased recycled aggregate concrete

Ruoyu Jin, Libo Yan, Alfred B.O. Soboyejo, Liang Huang, Bohumil Kasal

Research output: Contribution to journalArticle

Abstract

This study applied newly developed multivariate statistical models to estimating the mechanical properties of recycled aggregate concrete cylinder encased by fiber reinforced polymer (FRP). Two different types of RFPs were applied, namely flax FRP and polyester FRP. Ten independent variables were predefined including the FRP type and cylinder size. It was found that several mixed models outperformed the traditional linear regression approach, based on the accuracy and residual value distribution. Individual factor analysis indicated that the fiber thickness and layer number had more significant impacts on the strength and strain of FRP-encased concrete's transitional point, compared to their impacts at the ultimate state.

Original languageEnglish
Pages (from-to)216-227
Number of pages12
JournalConstruction and Building Materials
Volume191
DOIs
Publication statusPublished - 9 Oct 2018

Keywords

  • Fiber reinforced polymer (FRP)
  • Mechanical properties
  • Mixed model
  • Multivariate regression analysis
  • Recycled aggregate concrete (RAC)
  • Size effect
  • Slenderness
  • Statistical modeling

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