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Structural Engineering and Mechanics
  Volume 74, Number 4, May25 2020 , pages 503-514

Shear strength prediction for SFRC and UHPC beams using a Bayesian approach
Hae-Chang Cho, Min-Kook Park, Jin-Ha Hwang, Won-Hee Kang and Kang Su Kim

    This study proposes prediction models for the shear strength of steel fiber reinforced concrete (SFRC) and ultra-highperformance 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.
Key Words
    SFRC; UHPC; shear strength; steel fiber; bayesian parameter estimation
Hae-Chang Cho, Won-Hee Kang: Centre for Infrastructure Engineering, Western Sydney University, Penrith, NSW 2751, Australia
Min-Kook Park: Department of Civil and Environmental Engineering, Nazarbayev University, 53 Qabanbay Batyr Ave., Nul-sultan, 010000, Kazakhstan
Jin-Ha Hwang, and Kang Su Kim: Department of Architectural Engineering, University of Seoul, 163 Siripdaero, Dongdaemun-gu, Seoul 02504, Republic of Korea

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