Data-driven analysis on compressive behavior of unconfined and confined recycled aggregate concretes

Jinjun Xu, Wenguang Chen, Yong Yu, Jigang Xu, Xinyu Zhao

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

It is widely accepted that the inferior characteristics of recycled concrete aggregates (RCAs) reduce the mechanical properties of structural concrete and the available prediction models receive undesirable accuracies in estimating the compressive behavior of recycled aggregate concrete (RAC). To this end, this paper presents a series of data-driven analysis on unified modeling of the compressive behavior of unconfined and confined RACs. First, four reliable experimental databases containing the results of natural aggregate concrete (NAC) and RAC under uniaxial compression, RAC under triaxial compression, and fiber reinforced polymer (FRP)-confined RAC under axial compression were assembled through an extensive literature review, respectively. Based on the collected data, Mohr-Coulomb failure criterion was then employed to construct a model for estimation of the failure envelope of RAC under axial compression and different lateral active confinement stresses. Finally, unified models for predicting the compressive properties (i.e., compressive strength/peak stress and strain at peak stress) of unconfined and confined concretes incorporating natural aggregates (NAs) and/or RCAs were developed so as to provide a design-oriented procedure for material and structural assessments of both NAC and RAC. The results demonstrate that the proposed models exhibit acceptable predictions, thereby making various stakeholders gain sufficient confidence in use of RAC products.

Original languageEnglish
Article number129282
JournalConstruction and Building Materials
Volume356
DOIs
StatePublished - 21 Nov 2022

Keywords

  • Compressive strength
  • FRP-confined concrete
  • Failure criterion
  • Peak strain
  • Recycled aggregate concrete
  • Triaxial compression
  • Uniaxial compression
  • Unified model

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