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Shear strength prediction for SFRC and UHPC beams using a Bayesian approach

  • Cho, Hae-Chang (Centre for Infrastructure Engineering, Western Sydney University) ;
  • Park, Min-Kook (Department of Civil and Environmental Engineering, Nazarbayev University) ;
  • Hwang, Jin-Ha (Dpartment of Architectural Engineering, University of Seoul) ;
  • Kang, Won-Hee (Centre for Infrastructure Engineering, Western Sydney University) ;
  • Kim, Kang Su (Dpartment of Architectural Engineering, University of Seoul)
  • Received : 2019.03.13
  • Accepted : 2019.12.26
  • Published : 2020.05.25

Abstract

This study proposes prediction models for the shear strength of steel fiber reinforced concrete (SFRC) and ultra-high-performance fiber reinforced concrete (UHPC) beams using a Bayesian parameter estimation approach and a collected experimental database. Previous researchers had already proposed shear strength prediction models for SFRC and UHPC beams, but their performances were limited in terms of their prediction accuracies and the applicability to UHPC beams. Therefore, this study adopted a statistical approach based on a collected database to develop prediction models. In the database, 89 and 37 experimental data for SFRC and UHPC beams without stirrups were collected, respectively, and the proposed equations were developed using the Bayesian parameter estimation approach. The proposed models have a simplified form with important parameters, and in comparison to the existing prediction models, provide unbiased high prediction accuracy.

Keywords

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2018R1A4A1025953)

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